diff --git a/Calculators/Confusion-Matrix-Calculator/README.md b/Calculators/Confusion-Matrix-Calculator/README.md
new file mode 100644
index 000000000..c954e91e1
--- /dev/null
+++ b/Calculators/Confusion-Matrix-Calculator/README.md
@@ -0,0 +1,30 @@
+#
Confusion Matrix Calculator
+
+## Description :-
+
+An interactive web-based calculator that allows users to compute essential machine learning metrics based on a confusion matrix. By entering values for true positives, false positives, false negatives, and true negatives, users can instantly see calculated accuracy, precision, recall, and F1 score. These metrics are crucial for evaluating the performance of classification models in machine learning.
+
+## Tech Stacks :-
+
+- HTML
+- CSS
+- JavaScript
+
+## Features :-
+
+- Calculate accuracy, precision, recall, and F1 score based on confusion matrix inputs.
+- Instantly see performance metrics relevant to classification models.
+
+## Usage :-
+
+1. Open the index.html file in your web browser.
+
+2. Enter the following inputs:
+ - True Positive (TP)
+ - False Positive (FP)
+ - False Negative (FN)
+ - True Negative (TN)
+
+3. Click the "Calculate" button to view the computed metrics.
+
+The calculator will display accuracy, precision, recall, and F1 score based on the provided confusion matrix values.
diff --git a/Calculators/Confusion-Matrix-Calculator/assets/image.jpg b/Calculators/Confusion-Matrix-Calculator/assets/image.jpg
new file mode 100644
index 000000000..7161d95e1
Binary files /dev/null and b/Calculators/Confusion-Matrix-Calculator/assets/image.jpg differ
diff --git a/Calculators/Confusion-Matrix-Calculator/index.html b/Calculators/Confusion-Matrix-Calculator/index.html
new file mode 100644
index 000000000..5ba267f1c
--- /dev/null
+++ b/Calculators/Confusion-Matrix-Calculator/index.html
@@ -0,0 +1,75 @@
+
+
+
+
+
+ Confusion Matrix Calculator
+
+
+
+
+
+
+
Confusion Matrix Calculator
+
+
+
+
+
+
+
+
+
+
+
+
+
+
ACCURACY: (TP+TN)/(TP+TN+FP+FN)
+
PRECISION: TP/(TP+FP)
+
RECALL: TP/(TP+FN)
+
F1 SCORE: 2*((PRECISION+RECALL)/(PRECISON*RECALL))