diff --git a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
index d3cb2ca95285..cc6e0f04bcaf 100644
--- a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
+++ b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
@@ -1565,3 +1565,24 @@ def convert_hardsigmoid(node, **kwargs):
         name=name
     )
     return [node]
+
+@mx_op.register("broadcast_lesser")
+def convert_lesser(node, **kwargs):
+    """Map MXNet's broadcast_lesser operator attributes to onnx's Less operator
+    and return the created node.
+    """
+    return create_basic_op_node('Less', node, kwargs)
+
+@mx_op.register("broadcast_greater")
+def convert_greater(node, **kwargs):
+    """Map MXNet's broadcast_greater operator attributes to onnx's Greater operator
+    and return the created node.
+    """
+    return create_basic_op_node('Greater', node, kwargs)
+
+@mx_op.register("broadcast_equal")
+def convert_equal(node, **kwargs):
+    """Map MXNet's broadcast_equal operator attributes to onnx's Equal operator
+    and return the created node.
+    """
+    return create_basic_op_node('Equal', node, kwargs)
diff --git a/tests/python-pytest/onnx/export/mxnet_export_test.py b/tests/python-pytest/onnx/export/mxnet_export_test.py
index 9f91369d667e..161d50a5bd05 100644
--- a/tests/python-pytest/onnx/export/mxnet_export_test.py
+++ b/tests/python-pytest/onnx/export/mxnet_export_test.py
@@ -238,6 +238,63 @@ def test_square():
 
     npt.assert_almost_equal(result, numpy_op)
 
+@with_seed()
+def test_greater():
+    """Test for logical greater in onnx operators."""
+    input1 = np.random.rand(1, 3, 4, 5).astype("float32")
+    input2 = np.random.rand(1, 5).astype("float32")
+    inputs = [helper.make_tensor_value_info("input1", TensorProto.FLOAT, shape=np.shape(input1)),
+            helper.make_tensor_value_info("input2", TensorProto.FLOAT, shape=np.shape(input2))]
+    outputs = [helper.make_tensor_value_info("output", TensorProto.FLOAT, shape=np.shape(input1))]
+    nodes = [helper.make_node("Greater", ["input1", "input2"], ["output"])]
+    graph = helper.make_graph(nodes,
+                            "greater_test",
+                            inputs,
+                            outputs)
+    greater_model = helper.make_model(graph)
+    bkd_rep = backend.prepare(greater_model)
+    output = bkd_rep.run([input1, input2])
+    numpy_op = np.greater(input1, input2).astype(np.float32)
+    npt.assert_almost_equal(output[0], numpy_op)
+
+@with_seed()
+def test_equal():
+    """Test for equal in onnx operators."""
+    input1 = np.random.rand(1, 3, 4, 5).astype("float32")
+    input2 = np.random.rand(1, 5).astype("float32")
+    inputs = [helper.make_tensor_value_info("input1", TensorProto.FLOAT, shape=np.shape(input1)),
+            helper.make_tensor_value_info("input2", TensorProto.FLOAT, shape=np.shape(input2))]
+    outputs = [helper.make_tensor_value_info("output", TensorProto.FLOAT, shape=np.shape(input1))]
+    nodes = [helper.make_node("Equal", ["input1", "input2"], ["output"])]
+    graph = helper.make_graph(nodes,
+                            "equal_test",
+                            inputs,
+                            outputs)
+    equal_model = helper.make_model(graph)
+    bkd_rep = backend.prepare(equal_model)
+    output = bkd_rep.run([input1, input2])
+    numpy_op = np.equal(input1, input2).astype(np.float32)
+    npt.assert_almost_equal(output[0], numpy_op)
+
+@with_seed()
+def test_lesser():
+    """Test for lesser in onnx operators."""
+    input1 = np.random.rand(1, 3, 4, 5).astype("float32")
+    input2 = np.random.rand(1, 5).astype("float32")
+    inputs = [helper.make_tensor_value_info("input1", TensorProto.FLOAT, shape=np.shape(input1)),
+            helper.make_tensor_value_info("input2", TensorProto.FLOAT, shape=np.shape(input2))]
+    outputs = [helper.make_tensor_value_info("output", TensorProto.FLOAT, shape=np.shape(input1))]
+    nodes = [helper.make_node("Less", ["input1", "input2"], ["output"])]
+    graph = helper.make_graph(nodes,
+                            "less_test",
+                            inputs,
+                            outputs)
+    lesser_model = helper.make_model(graph)
+    bkd_rep = backend.prepare(lesser_model)
+    output = bkd_rep.run([input1, input2])
+    numpy_op = np.less(input1, input2).astype(np.float32)
+    npt.assert_almost_equal(output[0], numpy_op)
+
 if __name__ == '__main__':
     test_models("bvlc_googlenet", (1, 3, 224, 224), (1, 1000))
     test_models("bvlc_reference_caffenet", (1, 3, 224, 224), (1, 1000))