diff --git a/R/orsf_R6.R b/R/orsf_R6.R
index 864293e9..8c832576 100644
--- a/R/orsf_R6.R
+++ b/R/orsf_R6.R
@@ -732,11 +732,13 @@ ObliqueForest <- R6::R6Class(
                            pred_horizon = NULL,
                            pred_type = NULL,
                            importance_type = NULL,
+                           class = NULL,
                            verbose_progress = FALSE){
 
    # check incoming values if they were specified.
    private$check_n_variables(n_variables)
    private$check_verbose_progress(verbose_progress)
+   private$check_class(class)
 
    if(!is.null(pred_horizon)){
     private$check_pred_horizon(pred_horizon, boundary_checks = TRUE)
@@ -838,6 +840,13 @@ ObliqueForest <- R6::R6Class(
 
    if(self$tree_type == 'classification'){
     new_order <- insert_vals(new_order, 2, 'class')
+    if(!is.null(class)){
+     .class <- class # prevents mix-up with class in dt
+     pd_output <- pd_output[class == .class]
+    } else {
+     # put the highest level class on top
+     pd_output <- pd_output[order(-class)]
+    }
    }
 
    setcolorder(pd_output, new_order)
@@ -2153,6 +2162,27 @@ ObliqueForest <- R6::R6Class(
 
   },
 
+  check_class = function(class = NULL){
+
+   if(!is.null(class)){
+
+    check_arg_is(arg_value = class,
+                 arg_name = "class",
+                 expected_class = "character")
+
+    check_arg_length(arg_value = class,
+                     arg_name = "class",
+                     expected_length = 1L)
+
+    check_arg_is_valid(arg_value = class,
+                       arg_name = "class",
+                       valid_options = self$class_levels)
+
+   }
+
+
+  },
+
   # runs checks and sets defaults where needed.
   # data is NULL when we are creating a new forest,
   # but may be non-NULL if we update an existing one
diff --git a/R/orsf_summary.R b/R/orsf_summary.R
index a2024ffb..5680d94b 100644
--- a/R/orsf_summary.R
+++ b/R/orsf_summary.R
@@ -53,12 +53,20 @@
 #'
 #' orsf_summarize_uni(object, n_variables = 2, importance = 'negate')
 #'
+#' # for multi-category fits, you can specify which class
+#' # you want to summarize:
+#'
+#' fit =  orsf(species ~ ., data = penguins_orsf, n_tree = 25)
+#' orsf_summarize_uni(fit, class = "Adelie", n_variables = 1)
+#' orsf_summarize_uni(fit, class = "Gentoo", n_variables = 1)
+#'
 #'
 orsf_summarize_uni <- function(object,
                                n_variables = NULL,
                                pred_horizon = NULL,
                                pred_type = NULL,
                                importance = NULL,
+                               class = NULL,
                                verbose_progress = FALSE,
                                ...){
 
@@ -72,6 +80,7 @@ orsf_summarize_uni <- function(object,
                       pred_horizon    = pred_horizon,
                       pred_type       = pred_type,
                       importance_type = importance,
+                      class           = class,
                       verbose_progress = verbose_progress)
 
 }