diff --git a/runtime/onert/api/python/package/experimental/train/losses/__init__.py b/runtime/onert/api/python/package/experimental/train/losses/__init__.py
new file mode 100644
index 00000000000..12977444839
--- /dev/null
+++ b/runtime/onert/api/python/package/experimental/train/losses/__init__.py
@@ -0,0 +1,5 @@
+from .cce import CategoricalCrossentropy
+from .mse import MeanSquaredError
+from onert.native.libnnfw_api_pybind import lossinfo
+
+__all__ = ["CategoricalCrossentropy", "MeanSquaredError", "lossinfo", "loss"]
diff --git a/runtime/onert/api/python/package/experimental/train/losses/cce.py b/runtime/onert/api/python/package/experimental/train/losses/cce.py
new file mode 100644
index 00000000000..0fb1fa89729
--- /dev/null
+++ b/runtime/onert/api/python/package/experimental/train/losses/cce.py
@@ -0,0 +1,15 @@
+import numpy as np
+from .loss import LossFunction
+
+
+class CategoricalCrossentropy(LossFunction):
+    """
+    Categorical Cross-Entropy Loss Function with reduction type.
+    """
+    def __init__(self, reduction="mean"):
+        """
+        Initialize the Categorical Cross-Entropy loss function.
+        Args:
+            reduction (str): Reduction type ('mean', 'sum').
+        """
+        super().__init__(reduction)
diff --git a/runtime/onert/api/python/package/experimental/train/losses/loss.py b/runtime/onert/api/python/package/experimental/train/losses/loss.py
new file mode 100644
index 00000000000..0719ba68bfa
--- /dev/null
+++ b/runtime/onert/api/python/package/experimental/train/losses/loss.py
@@ -0,0 +1,24 @@
+from onert.native.libnnfw_api_pybind import loss_reduction
+
+
+class LossFunction:
+    """
+    Base class for loss functions with reduction type.
+    """
+    def __init__(self, reduction="mean"):
+        """
+        Initialize the Categorical Cross-Entropy loss function.
+        Args:
+            reduction (str): Reduction type ('mean', 'sum').
+        """
+        reduction_mapping = {
+            "mean": loss_reduction.SUM_OVER_BATCH_SIZE,
+            "sum": loss_reduction.SUM
+        }
+
+        # Validate and assign the reduction type
+        if reduction not in reduction_mapping:
+            raise ValueError(
+                f"Invalid reduction type. Choose from {list(reduction_mapping.keys())}.")
+
+        self.reduction = reduction_mapping[reduction]
diff --git a/runtime/onert/api/python/package/experimental/train/losses/mse.py b/runtime/onert/api/python/package/experimental/train/losses/mse.py
new file mode 100644
index 00000000000..ed9e37e3482
--- /dev/null
+++ b/runtime/onert/api/python/package/experimental/train/losses/mse.py
@@ -0,0 +1,15 @@
+import numpy as np
+from .loss import LossFunction
+
+
+class MeanSquaredError(LossFunction):
+    """
+    Mean Squared Error (MSE) Loss Function with reduction type.
+    """
+    def __init__(self, reduction="mean"):
+        """
+        Initialize the MSE loss function.
+        Args:
+            reduction (str): Reduction type ('mean', 'sum').
+        """
+        super().__init__(reduction)