diff --git a/ivy/functional/frontends/paddle/tensor/tensor.py b/ivy/functional/frontends/paddle/tensor/tensor.py
index c1c03b7a71207..d8a76e34a40c1 100644
--- a/ivy/functional/frontends/paddle/tensor/tensor.py
+++ b/ivy/functional/frontends/paddle/tensor/tensor.py
@@ -367,6 +367,40 @@ def logical_or(self, y, out=None, name=None):
     def bitwise_xor(self, y, out=None, name=None):
         return paddle_frontend.bitwise_xor(self, y)
 
+    @with_supported_dtypes(
+        {
+            "2.5.1 and below": (
+                "bool",
+                "int8",
+                "int16",
+                "int32",
+                "int64",
+                "float32",
+                "float64",
+            )
+        },
+        "paddle",
+    )
+    def logical_xor(self, y, out=None, name=None):
+        return paddle_frontend.logical_xor(self, y, out=out)
+
+    @with_supported_dtypes(
+        {
+            "2.5.1 and below": (
+                "float16",
+                "float32",
+                "float64",
+                "int8",
+                "int16",
+                "int32",
+                "int64",
+            )
+        },
+        "paddle",
+    )
+    def broadcast_tensors(self, name=None):
+        return paddle_frontend.Tensor(ivy.broadcast_arrays(self._ivy_array))
+
     @with_supported_dtypes({"2.5.1 and below": ("float16", "bfloat16")}, "paddle")
     def any(self, axis=None, keepdim=False, name=None):
         return paddle_frontend.any(self, axis=axis, keepdim=keepdim)
diff --git a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
index 2f6c9970003a0..740f495dbe982 100644
--- a/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_paddle/test_tensor/test_tensor.py
@@ -1128,6 +1128,46 @@ def test_paddle_tensor_bitwise_xor(
     )
 
 
+# broadcast_tensors
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="paddle.to_tensor",
+    method_name="broadcast_tensors",
+    dtype_x_axis=helpers.dtype_values_axis(
+        available_dtypes=helpers.get_dtypes("float"),
+        # valid_axis=True,
+        # force_int_axis=True,
+        # min_num_dims=1,
+        # min_value=-5,
+        # max_value=5,
+    ),
+)
+def test_paddle_tensor_broadcast_tensors(
+    dtype_x_axis,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x, axis = dtype_x_axis
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        init_all_as_kwargs_np={
+            "data": [x],
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={},
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # cast
 @handle_frontend_method(
     class_tree=CLASS_TREE,