diff --git a/R-package/R/xgb.plot.multi.trees.R b/R-package/R/xgb.plot.multi.trees.R
index 67a7a045172e..8b4f0eeed037 100644
--- a/R-package/R/xgb.plot.multi.trees.R
+++ b/R-package/R/xgb.plot.multi.trees.R
@@ -23,6 +23,7 @@
 #' @inheritParams xgb.plot.tree
 #' @param features_keep Number of features to keep in each position of the multi trees,
 #'   by default 5.
+#' @param render Should the graph be rendered or not? The default is `TRUE`.
 #' @inherit xgb.plot.tree return
 #'
 #' @examples
diff --git a/R-package/R/xgb.plot.tree.R b/R-package/R/xgb.plot.tree.R
index 881ea4fb3495..f5d53bb3432e 100644
--- a/R-package/R/xgb.plot.tree.R
+++ b/R-package/R/xgb.plot.tree.R
@@ -3,63 +3,38 @@
 #' Read a tree model text dump and plot the model.
 #'
 #' @details
-#' When using `style="xgboost"`, the content of each node is visualized as follows:
-#' - For non-terminal nodes, it will display the split condition (number or name if
-#'   available, and the condition that would decide to which node to go next).
-#' - Those nodes will be connected to their children by arrows that indicate whether the
-#'   branch corresponds to the condition being met or not being met.
+#' The content of each node is visualized as follows:
+#' - For non-terminal nodes, it will display the split condition (number or name
+#'   if available, and the condition that would decide to which node to go
+#'   next).
+#' - Those nodes will be connected to their children by arrows that indicate
+#'   whether the branch corresponds to the condition being met or not being met.
 #' - Terminal (leaf) nodes contain the margin to add when ending there.
 #'
-#' When using `style="R"`, the content of each node is visualized like this:
-#' - *Feature name*.
-#' - *Cover:* The sum of second order gradients of training data.
-#'   For the squared loss, this simply corresponds to the number of instances in the node.
-#'   The deeper in the tree, the lower the value.
-#' - *Gain* (for split nodes): Information gain metric of a split
-#'        (corresponds to the importance of the node in the model).
-#' - *Value* (for leaves): Margin value that the leaf may contribute to the prediction.
-#'
-#' The tree root nodes also indicate the tree index (0-based).
-#'
 #' The "Yes" branches are marked by the "< split_value" label.
 #' The branches also used for missing values are marked as bold
 #' (as in "carrying extra capacity").
 #'
-#' This function uses [GraphViz](https://www.graphviz.org/) as DiagrammeR backend.
+#' This function uses [GraphViz](https://www.graphviz.org/) as DiagrammeR
+#' backend.
 #'
-#' @param model Object of class `xgb.Booster`. If it contains feature names (they can be set through
-#'   [setinfo()], they will be used in the output from this function.
-#' @param trees An integer vector of tree indices that should be used.
-#'   The default (`NULL`) uses all trees.
-#'   Useful, e.g., in multiclass classification to get only
-#'   the trees of one class. *Important*: the tree index in XGBoost models
-#'   is zero-based (e.g., use `trees = 0:2` for the first three trees).
+#' @param model Object of class `xgb.Booster`. If it contains feature names
+#'   (they can be set through [setinfo()], they will be used in the
+#'   output from this function.
+#' @param tree_idx An integer of the tree index that should be used. This
+#'   is an 1-based index.
 #' @param plot_width,plot_height Width and height of the graph in pixels.
 #'   The values are passed to `DiagrammeR::render_graph()`.
-#' @param render Should the graph be rendered or not? The default is `TRUE`.
-#' @param show_node_id a logical flag for whether to show node id's in the graph.
-#' @param style Style to use for the plot:
-#'   - `"xgboost"`: will use the plot style defined in the core XGBoost library,
-#'     which is shared between different interfaces through the 'dot' format. This
-#'     style was not available before version 2.1.0 in R. It always plots the trees
-#'     vertically (from top to bottom).
-#'   - `"R"`: will use the style defined from XGBoost's R interface, which predates
-#'     the introducition of the standardized style from the core library. It might plot
-#'     the trees horizontally (from left to right).
-#'
-#'   Note that `style="xgboost"` is only supported when all of the following conditions are met:
-#'   - Only a single tree is being plotted.
-#'   - Node IDs are not added to the graph.
-#'   - The graph is being returned as `htmlwidget` (`render=TRUE`).
+#' @param with_stats Whether to dump some additional statistics about the
+#'   splits.  When this option is on, the model dump contains two additional
+#'   values: gain is the approximate loss function gain we get in each split;
+#'   cover is the sum of second order gradient in each node.
 #' @param ... Currently not used.
 #' @return
-#' The value depends on the `render` parameter:
-#' - If `render = TRUE` (default): Rendered graph object which is an htmlwidget of
-#'   class `grViz`. Similar to "ggplot" objects, it needs to be printed when not
-#'   running from the command line.
-#' - If `render = FALSE`: Graph object which is of DiagrammeR's class `dgr_graph`.
-#'   This could be useful if one wants to modify some of the graph attributes
-#'   before rendering the graph with `DiagrammeR::render_graph()`.
+#'
+#' Rendered graph object which is an htmlwidget of ' class `grViz`. Similar to
+#' "ggplot" objects, it needs to be printed when not running from the command
+#' line.
 #'
 #' @examples
 #' data(agaricus.train, package = "xgboost")
@@ -73,119 +48,35 @@
 #'   objective = "binary:logistic"
 #' )
 #'
-#' # plot the first tree, using the style from xgboost's core library
-#' # (this plot should look identical to the ones generated from other
-#' # interfaces like the python package for xgboost)
-#' xgb.plot.tree(model = bst, trees = 1, style = "xgboost")
-#'
-#' # plot all the trees
-#' xgb.plot.tree(model = bst, trees = NULL)
+#' # plot the first tree
+#' xgb.plot.tree(model = bst, tree_idx = 1)
 #'
-#' # plot only the first tree and display the node ID:
-#' xgb.plot.tree(model = bst, trees = 0, show_node_id = TRUE)
 #'
 #' \dontrun{
 #' # Below is an example of how to save this plot to a file.
-#' # Note that for export_graph() to work, the {DiagrammeRsvg}
-#' # and {rsvg} packages must also be installed.
 #'
 #' library(DiagrammeR)
 #'
-#' gr <- xgb.plot.tree(model = bst, trees = 0:1, render = FALSE)
-#' export_graph(gr, "tree.pdf", width = 1500, height = 1900)
-#' export_graph(gr, "tree.png", width = 1500, height = 1900)
+#' gr <- xgb.plot.tree(model = bst, tree_idx = 1)
+#' htmlwidgets::saveWidget(gr, 'plot.html')
 #' }
 #'
 #' @export
-xgb.plot.tree <- function(model = NULL, trees = NULL, plot_width = NULL, plot_height = NULL,
-                          render = TRUE, show_node_id = FALSE, style = c("R", "xgboost"), ...) {
+xgb.plot.tree <- function(model,
+                          tree_idx = 1,
+                          plot_width = NULL,
+                          plot_height = NULL,
+                          with_stats = FALSE, ...) {
   check.deprecation(...)
   if (!inherits(model, "xgb.Booster")) {
-    stop("model: Has to be an object of class xgb.Booster")
+    stop("model has to be an object of the class xgb.Booster")
   }
-
   if (!requireNamespace("DiagrammeR", quietly = TRUE)) {
-    stop("DiagrammeR package is required for xgb.plot.tree", call. = FALSE)
-  }
-
-  style <- as.character(head(style, 1L))
-  stopifnot(style %in% c("R", "xgboost"))
-  if (style == "xgboost") {
-    if (NROW(trees) != 1L || !render || show_node_id) {
-      stop("style='xgboost' is only supported for single, rendered tree, without node IDs.")
-    }
-
-    txt <- xgb.dump(model, dump_format = "dot")
-    return(DiagrammeR::grViz(txt[[trees + 1]], width = plot_width, height = plot_height))
-  }
-
-  dt <- xgb.model.dt.tree(model = model, trees = trees)
-
-  dt[, label := paste0(Feature, "\nCover: ", Cover, ifelse(Feature == "Leaf", "\nValue: ", "\nGain: "), Gain)]
-  if (show_node_id)
-    dt[, label := paste0(ID, ": ", label)]
-  dt[Node == 0, label := paste0("Tree ", Tree, "\n", label)]
-  dt[, shape := "rectangle"][Feature == "Leaf", shape := "oval"]
-  dt[, filledcolor := "Beige"][Feature == "Leaf", filledcolor := "Khaki"]
-  # in order to draw the first tree on top:
-  dt <- dt[order(-Tree)]
-
-  nodes <- DiagrammeR::create_node_df(
-    n         = nrow(dt),
-    ID        = dt$ID,
-    label     = dt$label,
-    fillcolor = dt$filledcolor,
-    shape     = dt$shape,
-    data      = dt$Feature,
-    fontcolor = "black")
-
-  if (nrow(dt[Feature != "Leaf"]) != 0) {
-    edges <- DiagrammeR::create_edge_df(
-      from  = match(rep(dt[Feature != "Leaf", c(ID)], 2), dt$ID),
-      to    = match(dt[Feature != "Leaf", c(Yes, No)], dt$ID),
-      label = c(
-        dt[Feature != "Leaf", paste("<", Split)],
-        rep("", nrow(dt[Feature != "Leaf"]))
-      ),
-      style = c(
-        dt[Feature != "Leaf", ifelse(Missing == Yes, "bold", "solid")],
-        dt[Feature != "Leaf", ifelse(Missing == No, "bold", "solid")]
-      ),
-      rel   = "leading_to")
-  } else {
-    edges <- NULL
+    stop("The DiagrammeR package is required for xgb.plot.tree", call. = FALSE)
   }
 
-  graph <- DiagrammeR::create_graph(
-      nodes_df = nodes,
-      edges_df = edges,
-      attr_theme = NULL
-  )
-  graph <- DiagrammeR::add_global_graph_attrs(
-      graph = graph,
-      attr_type = "graph",
-      attr  = c("layout", "rankdir"),
-      value = c("dot", "LR")
+  txt <- xgb.dump(model, dump_format = "dot", with_stats = with_stats)
+  DiagrammeR::grViz(
+    txt[[tree_idx]], width = plot_width, height = plot_height
   )
-  graph <- DiagrammeR::add_global_graph_attrs(
-      graph = graph,
-      attr_type = "node",
-      attr  = c("color", "style", "fontname"),
-      value = c("DimGray", "filled", "Helvetica")
-  )
-  graph <- DiagrammeR::add_global_graph_attrs(
-      graph = graph,
-      attr_type = "edge",
-      attr  = c("color", "arrowsize", "arrowhead", "fontname"),
-      value = c("DimGray", "1.5", "vee", "Helvetica")
-  )
-
-  if (!render) return(invisible(graph))
-
-  DiagrammeR::render_graph(graph, width = plot_width, height = plot_height)
 }
-
-# Avoid error messages during CRAN check.
-# The reason is that these variables are never declared
-# They are mainly column names inferred by Data.table...
-globalVariables(c("Feature", "ID", "Cover", "Gain", "Split", "Yes", "No", "Missing", ".", "shape", "filledcolor", "label"))
diff --git a/R-package/R/xgb.train.R b/R-package/R/xgb.train.R
index 4fb5c429c1a3..cafdde2da856 100644
--- a/R-package/R/xgb.train.R
+++ b/R-package/R/xgb.train.R
@@ -103,7 +103,7 @@
 #'      objective is non-convex.
 #'
 #'      See the tutorials [Custom Objective and Evaluation Metric](https://xgboost.readthedocs.io/en/stable/tutorials/custom_metric_obj.html)
-#'      and [Advanced Usage of Custom Objectives](https://xgboost.readthedocs.io/en/stable/tutorials/advanced_custom_obj)
+#'      and [Advanced Usage of Custom Objectives](https://xgboost.readthedocs.io/en/latest/tutorials/advanced_custom_obj.html)
 #'      for more information about custom objectives.
 #'
 #'   - `base_score`: The initial prediction score of all instances, global bias. Default: 0.5.
diff --git a/R-package/man/xgb.plot.multi.trees.Rd b/R-package/man/xgb.plot.multi.trees.Rd
index 6b165f9af113..df72ee452ee6 100644
--- a/R-package/man/xgb.plot.multi.trees.Rd
+++ b/R-package/man/xgb.plot.multi.trees.Rd
@@ -14,8 +14,9 @@ xgb.plot.multi.trees(
 )
 }
 \arguments{
-\item{model}{Object of class \code{xgb.Booster}. If it contains feature names (they can be set through
-\code{\link[=setinfo]{setinfo()}}, they will be used in the output from this function.}
+\item{model}{Object of class \code{xgb.Booster}. If it contains feature names
+(they can be set through \code{\link[=setinfo]{setinfo()}}, they will be used in the
+output from this function.}
 
 \item{features_keep}{Number of features to keep in each position of the multi trees,
 by default 5.}
@@ -28,15 +29,9 @@ The values are passed to \code{DiagrammeR::render_graph()}.}
 \item{...}{Currently not used.}
 }
 \value{
-The value depends on the \code{render} parameter:
-\itemize{
-\item If \code{render = TRUE} (default): Rendered graph object which is an htmlwidget of
-class \code{grViz}. Similar to "ggplot" objects, it needs to be printed when not
-running from the command line.
-\item If \code{render = FALSE}: Graph object which is of DiagrammeR's class \code{dgr_graph}.
-This could be useful if one wants to modify some of the graph attributes
-before rendering the graph with \code{DiagrammeR::render_graph()}.
-}
+Rendered graph object which is an htmlwidget of ' class \code{grViz}. Similar to
+"ggplot" objects, it needs to be printed when not running from the command
+line.
 }
 \description{
 Visualization of the ensemble of trees as a single collective unit.
diff --git a/R-package/man/xgb.plot.tree.Rd b/R-package/man/xgb.plot.tree.Rd
index cf0c2d0dd9eb..c58187d0f520 100644
--- a/R-package/man/xgb.plot.tree.Rd
+++ b/R-package/man/xgb.plot.tree.Rd
@@ -5,95 +5,57 @@
 \title{Plot boosted trees}
 \usage{
 xgb.plot.tree(
-  model = NULL,
-  trees = NULL,
+  model,
+  tree_idx = 1,
   plot_width = NULL,
   plot_height = NULL,
-  render = TRUE,
-  show_node_id = FALSE,
-  style = c("R", "xgboost"),
+  with_stats = FALSE,
   ...
 )
 }
 \arguments{
-\item{model}{Object of class \code{xgb.Booster}. If it contains feature names (they can be set through
-\code{\link[=setinfo]{setinfo()}}, they will be used in the output from this function.}
+\item{model}{Object of class \code{xgb.Booster}. If it contains feature names
+(they can be set through \code{\link[=setinfo]{setinfo()}}, they will be used in the
+output from this function.}
 
-\item{trees}{An integer vector of tree indices that should be used.
-The default (\code{NULL}) uses all trees.
-Useful, e.g., in multiclass classification to get only
-the trees of one class. \emph{Important}: the tree index in XGBoost models
-is zero-based (e.g., use \code{trees = 0:2} for the first three trees).}
+\item{tree_idx}{An integer of the tree index that should be used. This
+is an 1-based index.}
 
 \item{plot_width, plot_height}{Width and height of the graph in pixels.
 The values are passed to \code{DiagrammeR::render_graph()}.}
 
-\item{render}{Should the graph be rendered or not? The default is \code{TRUE}.}
-
-\item{show_node_id}{a logical flag for whether to show node id's in the graph.}
-
-\item{style}{Style to use for the plot:
-\itemize{
-\item \code{"xgboost"}: will use the plot style defined in the core XGBoost library,
-which is shared between different interfaces through the 'dot' format. This
-style was not available before version 2.1.0 in R. It always plots the trees
-vertically (from top to bottom).
-\item \code{"R"}: will use the style defined from XGBoost's R interface, which predates
-the introducition of the standardized style from the core library. It might plot
-the trees horizontally (from left to right).
-}
-
-Note that \code{style="xgboost"} is only supported when all of the following conditions are met:
-\itemize{
-\item Only a single tree is being plotted.
-\item Node IDs are not added to the graph.
-\item The graph is being returned as \code{htmlwidget} (\code{render=TRUE}).
-}}
+\item{with_stats}{Whether to dump some additional statistics about the
+splits.  When this option is on, the model dump contains two additional
+values: gain is the approximate loss function gain we get in each split;
+cover is the sum of second order gradient in each node.}
 
 \item{...}{Currently not used.}
 }
 \value{
-The value depends on the \code{render} parameter:
-\itemize{
-\item If \code{render = TRUE} (default): Rendered graph object which is an htmlwidget of
-class \code{grViz}. Similar to "ggplot" objects, it needs to be printed when not
-running from the command line.
-\item If \code{render = FALSE}: Graph object which is of DiagrammeR's class \code{dgr_graph}.
-This could be useful if one wants to modify some of the graph attributes
-before rendering the graph with \code{DiagrammeR::render_graph()}.
-}
+Rendered graph object which is an htmlwidget of ' class \code{grViz}. Similar to
+"ggplot" objects, it needs to be printed when not running from the command
+line.
 }
 \description{
 Read a tree model text dump and plot the model.
 }
 \details{
-When using \code{style="xgboost"}, the content of each node is visualized as follows:
+The content of each node is visualized as follows:
 \itemize{
-\item For non-terminal nodes, it will display the split condition (number or name if
-available, and the condition that would decide to which node to go next).
-\item Those nodes will be connected to their children by arrows that indicate whether the
-branch corresponds to the condition being met or not being met.
+\item For non-terminal nodes, it will display the split condition (number or name
+if available, and the condition that would decide to which node to go
+next).
+\item Those nodes will be connected to their children by arrows that indicate
+whether the branch corresponds to the condition being met or not being met.
 \item Terminal (leaf) nodes contain the margin to add when ending there.
 }
 
-When using \code{style="R"}, the content of each node is visualized like this:
-\itemize{
-\item \emph{Feature name}.
-\item \emph{Cover:} The sum of second order gradients of training data.
-For the squared loss, this simply corresponds to the number of instances in the node.
-The deeper in the tree, the lower the value.
-\item \emph{Gain} (for split nodes): Information gain metric of a split
-(corresponds to the importance of the node in the model).
-\item \emph{Value} (for leaves): Margin value that the leaf may contribute to the prediction.
-}
-
-The tree root nodes also indicate the tree index (0-based).
-
 The "Yes" branches are marked by the "< split_value" label.
 The branches also used for missing values are marked as bold
 (as in "carrying extra capacity").
 
-This function uses \href{https://www.graphviz.org/}{GraphViz} as DiagrammeR backend.
+This function uses \href{https://www.graphviz.org/}{GraphViz} as DiagrammeR
+backend.
 }
 \examples{
 data(agaricus.train, package = "xgboost")
@@ -107,27 +69,17 @@ bst <- xgb.train(
   objective = "binary:logistic"
 )
 
-# plot the first tree, using the style from xgboost's core library
-# (this plot should look identical to the ones generated from other
-# interfaces like the python package for xgboost)
-xgb.plot.tree(model = bst, trees = 1, style = "xgboost")
-
-# plot all the trees
-xgb.plot.tree(model = bst, trees = NULL)
+# plot the first tree
+xgb.plot.tree(model = bst, tree_idx = 1)
 
-# plot only the first tree and display the node ID:
-xgb.plot.tree(model = bst, trees = 0, show_node_id = TRUE)
 
 \dontrun{
 # Below is an example of how to save this plot to a file.
-# Note that for export_graph() to work, the {DiagrammeRsvg}
-# and {rsvg} packages must also be installed.
 
 library(DiagrammeR)
 
-gr <- xgb.plot.tree(model = bst, trees = 0:1, render = FALSE)
-export_graph(gr, "tree.pdf", width = 1500, height = 1900)
-export_graph(gr, "tree.png", width = 1500, height = 1900)
+gr <- xgb.plot.tree(model = bst, tree_idx = 1)
+htmlwidgets::saveWidget(gr, 'plot.html')
 }
 
 }
diff --git a/R-package/man/xgb.train.Rd b/R-package/man/xgb.train.Rd
index cbf7abf0f48b..be4290d9806d 100644
--- a/R-package/man/xgb.train.Rd
+++ b/R-package/man/xgb.train.Rd
@@ -129,7 +129,7 @@ the Hessian will be clipped, so one might consider using the expected Hessian (F
 objective is non-convex.
 
 See the tutorials \href{https://xgboost.readthedocs.io/en/stable/tutorials/custom_metric_obj.html}{Custom Objective and Evaluation Metric}
-and \href{https://xgboost.readthedocs.io/en/stable/tutorials/advanced_custom_obj}{Advanced Usage of Custom Objectives}
+and \href{https://xgboost.readthedocs.io/en/latest/tutorials/advanced_custom_obj.html}{Advanced Usage of Custom Objectives}
 for more information about custom objectives.
 \item \code{base_score}: The initial prediction score of all instances, global bias. Default: 0.5.
 \item \code{eval_metric}: Evaluation metrics for validation data.
diff --git a/R-package/tests/testthat/test_helpers.R b/R-package/tests/testthat/test_helpers.R
index 8ddba9519fc6..bfffe9e7878c 100644
--- a/R-package/tests/testthat/test_helpers.R
+++ b/R-package/tests/testthat/test_helpers.R
@@ -408,6 +408,19 @@ test_that("xgb.plot.tree works with and without feature names", {
   .skip_if_vcd_not_available()
   expect_silent(xgb.plot.tree(feature_names = feature.names, model = bst.Tree.unnamed))
   expect_silent(xgb.plot.tree(model = bst.Tree))
+
+  ## Categorical
+  y <- rnorm(100)
+  x <- sample(3, size = 100 * 3, replace = TRUE) |> matrix(nrow = 100)
+  x <- x - 1
+  dm <- xgb.DMatrix(data = x, label = y)
+  setinfo(dm, "feature_type", c("c", "c", "c"))
+  model <- xgb.train(
+    data = dm,
+    params = list(tree_method = "hist"),
+    nrounds = 2
+  )
+  expect_silent(xgb.plot.tree(model = model))
 })
 
 test_that("xgb.plot.multi.trees works with and without feature names", {
diff --git a/python-package/xgboost/core.py b/python-package/xgboost/core.py
index 05c0cc30fa82..c2034652322d 100644
--- a/python-package/xgboost/core.py
+++ b/python-package/xgboost/core.py
@@ -2994,7 +2994,7 @@ def get_dump(
         fmap :
             Name of the file containing feature map names.
         with_stats :
-            Controls whether the split statistics are output.
+            Controls whether the split statistics should be included.
         dump_format :
             Format of model dump. Can be 'text', 'json' or 'dot'.
 
diff --git a/python-package/xgboost/plotting.py b/python-package/xgboost/plotting.py
index ebb06b2afb11..552261c2d1a0 100644
--- a/python-package/xgboost/plotting.py
+++ b/python-package/xgboost/plotting.py
@@ -2,6 +2,7 @@
 # pylint: disable=too-many-branches
 """Plotting Library."""
 import json
+import warnings
 from io import BytesIO
 from typing import Any, Optional, Union
 
@@ -153,12 +154,14 @@ def to_graphviz(
     booster: Union[Booster, XGBModel],
     *,
     fmap: PathLike = "",
-    num_trees: int = 0,
+    num_trees: Optional[int] = None,
     rankdir: Optional[str] = None,
     yes_color: Optional[str] = None,
     no_color: Optional[str] = None,
     condition_node_params: Optional[dict] = None,
     leaf_node_params: Optional[dict] = None,
+    with_stats: bool = False,
+    tree_idx: int = 0,
     **kwargs: Any,
 ) -> GraphvizSource:
     """Convert specified tree to graphviz instance. IPython can automatically plot
@@ -172,7 +175,11 @@ def to_graphviz(
     fmap :
        The name of feature map file
     num_trees :
+
+        .. deprecated:: 3.0
+
         Specify the ordinal number of target tree
+
     rankdir :
         Passed to graphviz via graph_attr
     yes_color :
@@ -197,6 +204,18 @@ def to_graphviz(
              'style': 'filled',
              'fillcolor': '#e48038'}
 
+    with_stats :
+
+        .. versionadded:: 3.0
+
+        Controls whether the split statistics should be included.
+
+    tree_idx :
+
+        .. versionadded:: 3.0
+
+        Specify the ordinal index of target tree.
+
     kwargs :
         Other keywords passed to graphviz graph_attr, e.g. ``graph [ {key} = {value} ]``
 
@@ -243,35 +262,68 @@ def to_graphviz(
     if kwargs:
         parameters += ":"
         parameters += json.dumps(kwargs)
-    tree = booster.get_dump(fmap=fmap, dump_format=parameters)[num_trees]
+
+    if num_trees is not None:
+        warnings.warn(
+            "The `num_trees` parameter is deprecated, use `tree_idx` insetad. ",
+            FutureWarning,
+        )
+        if tree_idx not in (0, num_trees):
+            raise ValueError(
+                "Both `num_trees` and `tree_idx` are used, prefer `tree_idx` instead."
+            )
+        tree_idx = num_trees
+
+    tree = booster.get_dump(fmap=fmap, dump_format=parameters, with_stats=with_stats)[
+        tree_idx
+    ]
     g = Source(tree)
     return g
 
 
+@_deprecate_positional_args
 def plot_tree(
-    booster: Booster,
+    booster: Union[Booster, XGBModel],
+    *,
     fmap: PathLike = "",
-    num_trees: int = 0,
+    num_trees: Optional[int] = None,
     rankdir: Optional[str] = None,
     ax: Optional[Axes] = None,
+    with_stats: bool = False,
+    tree_idx: int = 0,
     **kwargs: Any,
 ) -> Axes:
     """Plot specified tree.
 
     Parameters
     ----------
-    booster : Booster, XGBModel
+    booster :
         Booster or XGBModel instance
     fmap: str (optional)
        The name of feature map file
-    num_trees : int, default 0
-        Specify the ordinal number of target tree
+    num_trees :
+
+        .. deprecated:: 3.0
+
     rankdir : str, default "TB"
         Passed to graphviz via graph_attr
     ax : matplotlib Axes, default None
         Target axes instance. If None, new figure and axes will be created.
+
+    with_stats :
+
+        .. versionadded:: 3.0
+
+        See :py:func:`to_graphviz`.
+
+    tree_idx :
+
+        .. versionadded:: 3.0
+
+        See :py:func:`to_graphviz`.
+
     kwargs :
-        Other keywords passed to to_graphviz
+        Other keywords passed to :py:func:`to_graphviz`
 
     Returns
     -------
@@ -287,7 +339,15 @@ def plot_tree(
     if ax is None:
         _, ax = plt.subplots(1, 1)
 
-    g = to_graphviz(booster, fmap=fmap, num_trees=num_trees, rankdir=rankdir, **kwargs)
+    g = to_graphviz(
+        booster,
+        fmap=fmap,
+        num_trees=num_trees,
+        rankdir=rankdir,
+        with_stats=with_stats,
+        tree_idx=tree_idx,
+        **kwargs,
+    )
 
     s = BytesIO()
     s.write(g.pipe(format="png"))
diff --git a/src/tree/tree_model.cc b/src/tree/tree_model.cc
index 2a5a40b970a1..040022c373a4 100644
--- a/src/tree/tree_model.cc
+++ b/src/tree/tree_model.cc
@@ -82,11 +82,11 @@ class TreeGenerator {
     }
     return res;
   }
-  /* \brief Find the first occurrence of key in input and replace it with corresponding
+  /* @brief Find the first occurrence of key in input and replace it with corresponding
    *        value.
    */
-  static std::string Match(std::string const& input,
-                           std::map<std::string, std::string> const& replacements) {
+  [[nodiscard]] static std::string Match(std::string const& input,
+                                         std::map<std::string, std::string> const& replacements) {
     std::string result = input;
     for (auto const& kv : replacements) {
       auto pos = result.find(kv.first);
@@ -671,16 +671,31 @@ class GraphvizGenerator : public TreeGenerator {
   std::string PlainNode(RegTree const& tree, bst_node_t nidx, uint32_t) const override {
     auto split_index = tree.SplitIndex(nidx);
     auto cond = tree.SplitCond(nidx);
-    static std::string const kNodeTemplate = "    {nid} [ label=\"{fname}{<}{cond}\" {params}]\n";
+    static std::string const kNodeTemplate =
+        "    {nid} [ label=\"{fname}{<}{cond}{stat}\" {params}]\n";
 
     bool has_less =
         (split_index >= fmap_.Size()) || fmap_.TypeOf(split_index) != FeatureMap::kIndicator;
-    std::string result =
-        SuperT::Match(kNodeTemplate, {{"{nid}", std::to_string(nidx)},
-                                      {"{fname}", GetFeatureName(fmap_, split_index)},
-                                      {"{<}", has_less ? "<" : ""},
-                                      {"{cond}", has_less ? ToStr(cond) : ""},
-                                      {"{params}", param_.condition_node_params}});
+    std::string result;
+    if (this->with_stats_) {
+      CHECK(!tree.IsMultiTarget()) << MTNotImplemented();
+      result = SuperT::Match(
+          kNodeTemplate, {{"{nid}", std::to_string(nidx)},
+                          {"{fname}", GetFeatureName(fmap_, split_index)},
+                          {"{<}", has_less ? "<" : ""},
+                          {"{cond}", has_less ? ToStr(cond) : ""},
+                          {"{stat}", Match("\ncover={cover}\ngain={gain}",
+                                           {{"{cover}", std::to_string(tree.Stat(nidx).sum_hess)},
+                                            {"{gain}", std::to_string(tree.Stat(nidx).loss_chg)}})},
+                          {"{params}", param_.condition_node_params}});
+    } else {
+      result = SuperT::Match(kNodeTemplate, {{"{nid}", std::to_string(nidx)},
+                                             {"{fname}", GetFeatureName(fmap_, split_index)},
+                                             {"{<}", has_less ? "<" : ""},
+                                             {"{cond}", has_less ? ToStr(cond) : ""},
+                                             {"{stat}", ""},
+                                             {"{params}", param_.condition_node_params}});
+    }
 
     result += BuildEdge<false>(tree, nidx, tree.LeftChild(nidx), true);
     result += BuildEdge<false>(tree, nidx, tree.RightChild(nidx), false);
@@ -708,21 +723,31 @@ class GraphvizGenerator : public TreeGenerator {
   }
 
   std::string LeafNode(RegTree const& tree, bst_node_t nidx, uint32_t) const override {
-    static std::string const kLeafTemplate = "    {nid} [ label=\"leaf={leaf-value}\" {params}]\n";
-    // hardcoded limit to avoid dumping long arrays into dot graph.
-    bst_target_t constexpr kLimit{3};
-    if (tree.IsMultiTarget()) {
-      auto value = tree.GetMultiTargetTree()->LeafValue(nidx);
-      auto result = SuperT::Match(kLeafTemplate, {{"{nid}", std::to_string(nidx)},
-                                                  {"{leaf-value}", ToStr(value, kLimit)},
-                                                  {"{params}", param_.leaf_node_params}});
-      return result;
+    static std::string const kCoverTemplate = "\ncover={cover}";
+    static std::string const kLeafTemplate =
+        "    {nid} [ label=\"leaf={leaf-value}{cover}\" {params}]\n";
+    auto plot = [&](std::string cover) {
+      if (tree.IsMultiTarget()) {
+        auto value = tree.GetMultiTargetTree()->LeafValue(nidx);
+        // Hardcoded limit to avoid dumping long arrays into dot graph.
+        bst_target_t constexpr kLimit{3};
+        return SuperT::Match(kLeafTemplate, {{"{nid}", std::to_string(nidx)},
+                                             {"{leaf-value}", ToStr(value, kLimit)},
+                                             {"{cover}", std::move(cover)},
+                                             {"{params}", param_.leaf_node_params}});
+      } else {
+        auto value = tree[nidx].LeafValue();
+        return SuperT::Match(kLeafTemplate, {{"{nid}", std::to_string(nidx)},
+                                             {"{leaf-value}", ToStr(value)},
+                                             {"{cover}", std::move(cover)},
+                                             {"{params}", param_.leaf_node_params}});
+      }
+    };
+    if (this->with_stats_) {
+      CHECK(!tree.IsMultiTarget()) << MTNotImplemented();
+      return plot(SuperT::Match(kCoverTemplate, {{"{cover}", ToStr(tree.Stat(nidx).sum_hess)}}));
     } else {
-      auto value = tree[nidx].LeafValue();
-      auto result = SuperT::Match(kLeafTemplate, {{"{nid}", std::to_string(nidx)},
-                                                  {"{leaf-value}", ToStr(value)},
-                                                  {"{params}", param_.leaf_node_params}});
-      return result;
+      return plot("");
     }
   }
 
diff --git a/tests/cpp/tree/test_multi_target_tree_model.cc b/tests/cpp/tree/test_multi_target_tree_model.cc
index 39e4cb4b52f0..2f01e05de0e2 100644
--- a/tests/cpp/tree/test_multi_target_tree_model.cc
+++ b/tests/cpp/tree/test_multi_target_tree_model.cc
@@ -60,7 +60,7 @@ TEST(MultiTargetTree, DumpDot) {
     auto name = "feat_" + std::to_string(f);
     fmap.PushBack(f, name.c_str(), "q");
   }
-  auto str = tree->DumpModel(fmap, true, "dot");
+  auto str = tree->DumpModel(fmap, false, "dot");
   ASSERT_NE(str.find("leaf=[2, 3, 4]"), std::string::npos);
   ASSERT_NE(str.find("leaf=[3, 4, 5]"), std::string::npos);
 
@@ -71,7 +71,7 @@ TEST(MultiTargetTree, DumpDot) {
     linalg::Vector<float> weight{{1.0f, 2.0f, 3.0f, 4.0f}, {4ul}, DeviceOrd::CPU()};
     tree.ExpandNode(RegTree::kRoot, /*split_idx=*/1, 0.5f, true, weight.HostView(),
                     weight.HostView(), weight.HostView());
-    auto str = tree.DumpModel(fmap, true, "dot");
+    auto str = tree.DumpModel(fmap, false, "dot");
     ASSERT_NE(str.find("leaf=[1, 2, ..., 4]"), std::string::npos);
   }
 }
diff --git a/tests/cpp/tree/test_tree_model.cc b/tests/cpp/tree/test_tree_model.cc
index 2dc1893dd645..941c425bd9b0 100644
--- a/tests/cpp/tree/test_tree_model.cc
+++ b/tests/cpp/tree/test_tree_model.cc
@@ -1,11 +1,12 @@
-// Copyright by Contributors
+/**
+ * Copyright 2018-2024, XGBoost Contributors
+ */
 #include <gtest/gtest.h>
 
 #include "../../../src/common/bitfield.h"
 #include "../../../src/common/categorical.h"
 #include "../filesystem.h"
 #include "../helpers.h"
-#include "xgboost/json_io.h"
 #include "xgboost/tree_model.h"
 
 namespace xgboost {
@@ -449,7 +450,8 @@ TEST(Tree, DumpDot) {
   fmap.PushBack(2, "feat_2", "int");
 
   str = tree.DumpModel(fmap, true, "dot");
-  ASSERT_NE(str.find(R"("feat_0")"), std::string::npos);
+  ASSERT_NE(str.find(R"("feat_0)"), std::string::npos);
+  ASSERT_EQ(str.find(R"("feat_0")"), std::string::npos);  // newline
   ASSERT_NE(str.find(R"(feat_1<1)"), std::string::npos);
   ASSERT_NE(str.find(R"(feat_2<2)"), std::string::npos);
 
diff --git a/tests/python/test_plotting.py b/tests/python/test_plotting.py
index aaf896c6945f..1e1311c5750f 100644
--- a/tests/python/test_plotting.py
+++ b/tests/python/test_plotting.py
@@ -54,10 +54,10 @@ def test_plotting(self):
         assert ax.patches[2].get_facecolor() == (0, 0, 1.0, 1.0)  # blue
         assert ax.patches[3].get_facecolor() == (0, 0, 1.0, 1.0)  # blue
 
-        g = xgb.to_graphviz(booster, num_trees=0)
+        g = xgb.to_graphviz(booster, tree_idx=0)
         assert isinstance(g, Source)
 
-        ax = xgb.plot_tree(booster, num_trees=0)
+        ax = xgb.plot_tree(booster, tree_idx=0)
         assert isinstance(ax, Axes)
 
     def test_importance_plot_lim(self):
@@ -86,9 +86,9 @@ def run_categorical(self, tree_method: str) -> None:
                 j_tree["split_condition"], list
             )
 
-        graph = xgb.to_graphviz(reg, num_trees=len(j_tree) - 1)
+        graph = xgb.to_graphviz(reg, tree_idx=len(j_tree) - 1)
         assert isinstance(graph, Source)
-        ax = xgb.plot_tree(reg, num_trees=len(j_tree) - 1)
+        ax = xgb.plot_tree(reg, tree_idx=len(j_tree) - 1)
         assert isinstance(ax, Axes)
 
     @pytest.mark.skipif(**tm.no_pandas())