diff --git a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
index 3576242e0d77..c1c150fe7405 100644
--- a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
+++ b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
@@ -1122,19 +1122,19 @@ def convert_dropout(node, **kwargs):
     """
     from onnx.helper import make_node
     name, input_nodes, attrs = get_inputs(node, kwargs)
-    opset_version = kwargs["opset_version"]
 
-    probability = float(attrs.get("p", 0.5))
+    _ = float(attrs.get("p", 0.5))
+    _ = convert_string_to_list(attrs.get("axes", "None"))
+    mode = attrs.get('mode', 'training')
 
-    if opset_version >= 12:
-        # opset >= 12 requires the ratio to be an input
-        nodes = [
-            create_const_scalar_node(name+"_ratio0", np.float32(probability), kwargs),
-            make_node("Dropout", [input_nodes[0], name+"_ratio0"], [name], name=name)
-        ]
-        return nodes
-    else:
-        return [make_node("Dropout", input_nodes, [name], ratio=probability, name=name)]
+    if mode != 'training':
+        raise NotImplementedError("Dropout does not currently support mode!=\'training\'")
+
+    nodes = [
+        make_node('Identity', [input_nodes[0]], [name])
+    ]
+
+    return nodes
 
 
 @mx_op.register("Flatten")
diff --git a/tests/python-pytest/onnx/test_operators.py b/tests/python-pytest/onnx/test_operators.py
index f4b44e58f188..53850fd9fbb5 100644
--- a/tests/python-pytest/onnx/test_operators.py
+++ b/tests/python-pytest/onnx/test_operators.py
@@ -896,6 +896,15 @@ def test_onnx_export_broadcast_mul(tmp_path, dtype):
     op_export_test('broadcast_mul', M, [x, y], tmp_path)
 
 
+@pytest.mark.parametrize('dtype', ['float16', 'float32', 'float64'])
+@pytest.mark.parametrize('shape', [(3, 4, 5), (1, 2, 3, 2, 1)])
+@pytest.mark.parametrize('p', [0, 0.1, 0.5, 1])
+def test_onnx_export_dropout(tmp_path, dtype, shape, p):
+    x = mx.random.uniform(-100, 100, shape=shape).astype(dtype)
+    M = def_model('Dropout', p=p)
+    op_export_test('Dropuout', M, [x], tmp_path)
+
+
 @pytest.mark.parametrize('dtype', ['float32'])
 @pytest.mark.parametrize('shape', [(1, 3, 64, 64), (2, 6, 60, 60)])
 @pytest.mark.parametrize('num_filter', [2, 4, 32])