diff --git a/Machine_Learning/convert_onnx.py b/Machine_Learning/convert_onnx.py
new file mode 100644
index 0000000..b2a0eb2
--- /dev/null
+++ b/Machine_Learning/convert_onnx.py
@@ -0,0 +1,61 @@
+#!/usr/bin/env python3
+"""Convert TensorFlow SavedModel to ONNX format."""
+
+import argparse
+import subprocess
+import sys
+from pathlib import Path
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Convert TensorFlow SavedModel to ONNX format"
+    )
+    parser.add_argument(
+        "--saved-model",
+        type=Path,
+        default=Path("model/saved_model"),
+        help="Path to the TensorFlow SavedModel directory",
+    )
+    parser.add_argument(
+        "--output",
+        type=Path,
+        default=Path("model/model.onnx"),
+        help="Path to the output ONNX model file",
+    )
+    parser.add_argument(
+        "--opset",
+        type=int,
+        default=13,
+        help="ONNX opset version to target",
+    )
+
+    args = parser.parse_args()
+
+    # Check that saved model exists
+    if not args.saved_model.exists():
+        raise FileNotFoundError(f"SavedModel not found at {args.saved_model}")
+
+    # Create output parent directory if needed
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+
+    # Run tf2onnx conversion
+    cmd = [
+        sys.executable,
+        "-m",
+        "tf2onnx.convert",
+        "--saved-model",
+        str(args.saved_model),
+        "--output",
+        str(args.output),
+        "--opset",
+        str(args.opset),
+    ]
+
+    subprocess.run(cmd, check=True)
+
+    print(f"ONNX model saved to {args.output}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/Machine_Learning/requirements.txt b/Machine_Learning/requirements.txt
index 4094d4d..5f539d9 100644
--- a/Machine_Learning/requirements.txt
+++ b/Machine_Learning/requirements.txt
@@ -2,3 +2,6 @@ tensorflow>=2.13.0
 tensorflowjs>=4.10.0
 jupyter>=1.0.0
 ipykernel>=6.25.0
+tf2onnx>=1.16.1
+onnx>=1.16.0
+onnxruntime>=1.17.0