diff --git a/causal_curve/core.py b/causal_curve/core.py
index a2b332c..bd492b1 100644
--- a/causal_curve/core.py
+++ b/causal_curve/core.py
@@ -10,7 +10,9 @@ class Core:
     """Base class for causal_curve module"""
 
     def __init__(self):
-        __version__ = "1.0.2"
+        pass
+
+    __version__ = "1.0.3"
 
     def get_params(self):
         """Returns a dict of all of the object's user-facing parameters
diff --git a/causal_curve/gps_core.py b/causal_curve/gps_core.py
index 0e895bc..57bb899 100644
--- a/causal_curve/gps_core.py
+++ b/causal_curve/gps_core.py
@@ -412,6 +412,8 @@ def fit(self, T, X, y):
         self : object
 
         """
+        self.rand_seed_wrapper(self.random_seed)
+
         self.T = T.reset_index(drop=True, inplace=False)
         self.X = X.reset_index(drop=True, inplace=False)
         self.y = y.reset_index(drop=True, inplace=False)
@@ -481,6 +483,7 @@ def calculate_CDRC(self, ci=0.95):
         self: object
 
         """
+        self.rand_seed_wrapper(self.random_seed)
         self._validate_calculate_CDRC_params(ci)
 
         self.if_verbose_print(
diff --git a/causal_curve/mediation.py b/causal_curve/mediation.py
index bc44b7f..c23dea4 100644
--- a/causal_curve/mediation.py
+++ b/causal_curve/mediation.py
@@ -389,6 +389,8 @@ def fit(self, T, M, y):
         self : object
 
         """
+        self.rand_seed_wrapper(self.random_seed)
+
         self.T = T.reset_index(drop=True, inplace=False)
         self.M = M.reset_index(drop=True, inplace=False)
         self.y = y.reset_index(drop=True, inplace=False)
@@ -445,6 +447,7 @@ def calculate_mediation(self, ci=0.95):
         self : object
 
         """
+        self.rand_seed_wrapper(self.random_seed)
 
         # Collect effect results in these lists
         self.t_bin_means = self._collect_mean_t_levels()
diff --git a/causal_curve/tmle_core.py b/causal_curve/tmle_core.py
index fa31970..72e0a56 100644
--- a/causal_curve/tmle_core.py
+++ b/causal_curve/tmle_core.py
@@ -340,6 +340,8 @@ def fit(self, T, X, y):
         self : object
 
         """
+        self.rand_seed_wrapper(self.random_seed)
+
         self.t_data = T.reset_index(drop=True, inplace=False)
         self.x_data = X.reset_index(drop=True, inplace=False)
         self.y_data = y.reset_index(drop=True, inplace=False)
@@ -407,6 +409,8 @@ def calculate_CDRC(self, ci=0.95):
         self: object
 
         """
+        self.rand_seed_wrapper(self.random_seed)
+
         self._validate_calculate_CDRC_params(ci)
 
         self.if_verbose_print("""
diff --git a/docs/changelog.rst b/docs/changelog.rst
index 6d68649..d3bb0c0 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -5,6 +5,10 @@ Change Log
 ==========
 
 
+Version 1.0.3
+-------------
+- Fixed bug with `random_seed` functionality in all tools
+
 Version 1.0.2
 -------------
 - Updated end-to-end example notebook in `/examples` folder
diff --git a/docs/conf.py b/docs/conf.py
index e54ed56..d1fc56b 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -23,7 +23,7 @@
 author = "Roni Kobrosly"
 
 # The full version, including alpha/beta/rc tags
-release = "1.0.2"
+release = "1.0.3"
 
 # -- General configuration ---------------------------------------------------
 
diff --git a/examples/NHANES_BLL_example.ipynb b/examples/NHANES_BLL_example.ipynb
index c99b5d7..681ed0e 100644
--- a/examples/NHANES_BLL_example.ipynb
+++ b/examples/NHANES_BLL_example.ipynb
@@ -635,7 +635,7 @@
       "    'lower_grid_constraint': 0.01,\n",
       "    'max_iter': 100,\n",
       "    'n_splines': 5,\n",
-      "    'random_seed': None,\n",
+      "    'random_seed': 111,\n",
       "    'spline_order': 3,\n",
       "    'treatment_grid_num': 10,\n",
       "    'upper_grid_constraint': 0.99,\n",
@@ -653,7 +653,7 @@
       "\n",
       "\n",
       "Mean indirect effect proportion:\n",
-      "            0.2021 (0.1916 - 0.2576)\n",
+      "            0.1979 (0.1908 - 0.3205)\n",
       "            \n"
      ]
     }
@@ -664,6 +664,7 @@
     "    bootstrap_replicates=100,\n",
     "    spline_order=3,\n",
     "    n_splines=5,\n",
+    "    random_seed=111,\n",
     "    verbose=True,\n",
     ")\n",
     "\n",
@@ -694,7 +695,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1200x1000 with 1 Axes>"
       ]
diff --git a/setup.py b/setup.py
index 648a129..15a26f6 100644
--- a/setup.py
+++ b/setup.py
@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="causal-curve",
-    version="1.0.2",
+    version="1.0.3",
     author="Roni Kobrosly",
     author_email="roni.kobrosly@gmail.com",
     description="A python library with tools to perform causal inference using \