diff --git a/ivy/data_classes/array/experimental/manipulation.py b/ivy/data_classes/array/experimental/manipulation.py
index 013af82658b0a..74dcc59192d7d 100644
--- a/ivy/data_classes/array/experimental/manipulation.py
+++ b/ivy/data_classes/array/experimental/manipulation.py
@@ -1134,6 +1134,64 @@ def take(
             self, indices, axis=axis, mode=mode, fill_value=fill_value, out=out
         )
 
+    def unflatten(
+        x: Union[int, ivy.Array, ivy.NativeArray],
+        /,
+        *,
+        dim: Optional[int] = 0,
+        shape: Union[Tuple[int], ivy.Array, ivy.NativeArray],
+        out: Optional[ivy.Array] = None,
+        mode: str = "fill",
+        fill_value: Optional[Number] = None,
+    ) -> ivy.Array:
+        """ivy.Array instance method variant of ivy.unflatten. This method
+        simply wraps the function, and so the docstring for ivy.unflatten also
+        applies to this method with minimal changes.
+
+        Parameters
+        ----------
+        x
+            input array
+        shape
+            array indices. Must have an integer data type.
+        dim
+            axis over which to unflatten. If `axis` is negative,
+            the function must determine the axis along which to select values
+            by counting from the last dimension.
+            By default, the flattened input array is used.
+        out
+            optional output array, for writing the result to. It must
+            have a shape that the inputs broadcast to.
+
+        Returns
+        -------
+            ret
+                an array having the same data type as `x`.
+                The output array must have the same rank
+                (i.e., number of dimensions) as `x` and
+                must have the same shape as `x`,
+                except for the axis specified by `dim`
+                which is replaced with a tuple specified in `shape`.
+
+
+        Examples
+        --------
+        With 'ivy.Array' input:
+
+        >>> x = ivy.array([[1.2, 2.3, 3.4, 4.5],
+                           [5.6, 6.7, 7.8, 8.9]])
+        >>> shape = (2, 2)
+        >>> y = ivy.unflatten(x, shape=shape, dim=dim, out=y)
+        >>> print(y)
+        ivy.array([[[1.2, 2.3], [3.4, 4.5]], [[5.6, 6.7], [7.8, 8.9]]])
+        """
+        return ivy.unflatten(
+            x,
+            dim=dim,
+            shape=shape,
+            out=out,
+        )
+
     def trim_zeros(
         self: ivy.Array,
         /,