diff --git a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
index 57ef546de29f..ce20b7da4418 100644
--- a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
+++ b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
@@ -2784,6 +2784,47 @@ def convert_arange(node, **kwargs):
     return nodes
 
 
+@mx_op.register("reverse")
+def convert_reverse(node, **kwargs):
+    """Map MXNet's reverse operator attributes to ONNX
+    """
+    from onnx.helper import make_node
+    name, input_nodes, attrs = get_inputs(node, kwargs)
+
+    axis = int(attrs.get('axis', 0))
+
+    # Transpose takes perm as a parameter, so we must 'pad' the input to a known dim (10 here)
+    perm = [i for i in range(10)]
+    perm[0], perm[axis] = axis, 0
+
+    nodes = [
+        create_tensor([10], name+'_10', kwargs['initializer']),
+        create_tensor([0], name+'_0', kwargs['initializer']),
+        create_tensor([1], name+'_1', kwargs['initializer']),
+        create_tensor([-1], name+'_m1', kwargs['initializer']),
+        create_tensor([axis], name+'_axis', kwargs['initializer']),
+        create_tensor([axis+1], name+'_axis_p1', kwargs['initializer']),
+        create_tensor([], name+'_void', kwargs['initializer']),
+        create_const_scalar_node(name+'_m1_s', np.array([-1], dtype='int64'), kwargs),
+        make_node('Shape', [input_nodes[0]], [name+'_shape']),
+        make_node('Shape', [name+'_shape'], [name+'_dim']),
+        make_node('Sub', [name+'_10', name+'_dim'], [name+'_sub']),
+        make_node('Concat', [name+'_0', name+'_sub'], [name+'_concat'], axis=0),
+        make_node('Pad', [name+'_shape', name+'_concat', name+'_1'], [name+'_shape_10_dim']),
+        make_node('Reshape', [input_nodes[0], name+'_shape_10_dim'], [name+'_data_10_dim']),
+        make_node('Transpose', [name+'_data_10_dim'], [name+'_data_t'], perm=perm),
+        make_node('Slice', [name+'_shape', name+'_axis', name+'_axis_p1'], [name+'_axis_len']),
+        make_node('Sub', [name+'_axis_len', name+'_1'], [name+'_axis_len_m1']),
+        make_node('Reshape', [name+'_axis_len_m1', name+'_void'], [name+'_axis_len_m1_s']),
+        make_node('Range', [name+'_axis_len_m1_s', name+'_m1_s', name+'_m1_s'], [name+'_indices']),
+        make_node('Gather', [name+'_data_t', name+'_indices'], [name+'_gather']),
+        make_node('Transpose', [name+'_gather'], [name+'_data_reversed'], perm=perm),
+        make_node('Reshape', [name+'_data_reversed', name+'_shape'], [name], name=name)
+        ]
+
+    return nodes
+
+
 @mx_op.register('repeat')
 def convert_repeat(node, **kwargs):
     """Map MXNet's repeat operator attributes to onnx's Tile operator.
diff --git a/tests/python-pytest/onnx/test_operators.py b/tests/python-pytest/onnx/test_operators.py
index c17a03bc3276..2efa582d4c95 100644
--- a/tests/python-pytest/onnx/test_operators.py
+++ b/tests/python-pytest/onnx/test_operators.py
@@ -353,6 +353,14 @@ def test_onnx_export_softmax(tmp_path, dtype):
     op_export_test('softmax_4', M4, [x, l4], tmp_path)
 
 
+@pytest.mark.parametrize('dtype', ['float16', 'float32', 'float64', 'int32', 'int64'])
+@pytest.mark.parametrize('axis', [0, 1, 2, 3])
+def test_onnx_export_reverse(tmp_path, dtype, axis):
+    x = mx.nd.arange(0, 120, dtype=dtype).reshape((2, 3, 4, 5))
+    M = def_model('reverse', axis=axis)
+    op_export_test('reverse', M, [x], tmp_path)
+
+
 @pytest.mark.parametrize('dtype', ['float16', 'float32', 'float64', 'int32', 'int64'])
 @pytest.mark.parametrize('axis', [None, 0, 1, 2, -1, -2, -3])
 @pytest.mark.parametrize('repeats', [2, 1, 3])