diff --git a/zeta/nn/modules/fractoral_norm.py b/zeta/nn/modules/fractoral_norm.py
new file mode 100644
index 00000000..bf4ccf84
--- /dev/null
+++ b/zeta/nn/modules/fractoral_norm.py
@@ -0,0 +1,32 @@
+from torch import nn, Tensor
+
+
+class FractoralNorm(nn.Module):
+    """
+    FractoralNorm module applies LayerNorm to the input tensor multiple times in a row.
+
+    Args:
+        num_features (int): Number of features in the input tensor.
+        depth (int): Number of times to apply LayerNorm.
+    """
+
+    def __init__(self, num_features: int, depth: int):
+        super().__init__()
+
+        self.layers = nn.ModuleList(
+            [nn.LayerNorm(num_features) for _ in range(depth)]
+        )
+
+    def forward(self, x: Tensor) -> Tensor:
+        """
+        Forward pass of the FractoralNorm module.
+
+        Args:
+            x (Tensor): Input tensor.
+
+        Returns:
+            Tensor: Output tensor after applying LayerNorm multiple times.
+        """
+        for layer in self.layers:
+            x = layer(x)
+        return x