diff --git a/nbs/core.ipynb b/nbs/core.ipynb
index 459ed1a78..54c5de3d9 100644
--- a/nbs/core.ipynb
+++ b/nbs/core.ipynb
@@ -523,7 +523,7 @@
     "\n",
     "        # Declare predictions pd.DataFrame\n",
     "        if df_constructor is pl_DataFrame:\n",
-    "            fcsts = pl_DataFrame(fcsts, schema=cols)\n",
+    "            fcsts = pl_DataFrame(dict(zip(cols, fcsts.T)))\n",
     "        else:\n",
     "            fcsts = pd.DataFrame(fcsts, columns=cols)\n",
     "        fcsts_df = ufp.horizontal_concat([fcsts_df, fcsts])\n",
@@ -654,7 +654,7 @@
     "\n",
     "        # Add predictions to forecasts DataFrame\n",
     "        if isinstance(self.uids, pl_Series):\n",
-    "            fcsts = pl_DataFrame(fcsts, schema=cols)\n",
+    "            fcsts = pl_DataFrame(dict(zip(cols, fcsts.T)))\n",
     "        else:\n",
     "            fcsts = pd.DataFrame(fcsts, columns=cols)\n",
     "        fcsts_df = ufp.horizontal_concat([fcsts_df, fcsts])\n",
@@ -752,7 +752,7 @@
     "\n",
     "        # Add predictions to forecasts DataFrame\n",
     "        if isinstance(self.uids, pl_Series):\n",
-    "            fcsts = pl_DataFrame(fcsts, schema=cols)\n",
+    "            fcsts = pl_DataFrame(dict(zip(cols, fcsts.T)))\n",
     "            Y_df = pl_DataFrame(original_y)\n",
     "        else:\n",
     "            fcsts = pd.DataFrame(fcsts, columns=cols)\n",
diff --git a/neuralforecast/core.py b/neuralforecast/core.py
index ab136fcb4..87d39796e 100644
--- a/neuralforecast/core.py
+++ b/neuralforecast/core.py
@@ -443,7 +443,7 @@ def predict(
 
         # Declare predictions pd.DataFrame
         if df_constructor is pl_DataFrame:
-            fcsts = pl_DataFrame(fcsts, schema=cols)
+            fcsts = pl_DataFrame(dict(zip(cols, fcsts.T)))
         else:
             fcsts = pd.DataFrame(fcsts, columns=cols)
         fcsts_df = ufp.horizontal_concat([fcsts_df, fcsts])
@@ -582,7 +582,7 @@ def cross_validation(
 
         # Add predictions to forecasts DataFrame
         if isinstance(self.uids, pl_Series):
-            fcsts = pl_DataFrame(fcsts, schema=cols)
+            fcsts = pl_DataFrame(dict(zip(cols, fcsts.T)))
         else:
             fcsts = pd.DataFrame(fcsts, columns=cols)
         fcsts_df = ufp.horizontal_concat([fcsts_df, fcsts])
@@ -688,7 +688,7 @@ def predict_insample(self, step_size: int = 1):
 
         # Add predictions to forecasts DataFrame
         if isinstance(self.uids, pl_Series):
-            fcsts = pl_DataFrame(fcsts, schema=cols)
+            fcsts = pl_DataFrame(dict(zip(cols, fcsts.T)))
             Y_df = pl_DataFrame(original_y)
         else:
             fcsts = pd.DataFrame(fcsts, columns=cols)