diff --git a/ctlearn/tools/predict_model.py b/ctlearn/tools/predict_model.py
index afca2380..0eaa8b23 100644
--- a/ctlearn/tools/predict_model.py
+++ b/ctlearn/tools/predict_model.py
@@ -18,6 +18,7 @@
     vstack,
     join,
     setdiff,
+    unique,
 )
 
 from ctapipe.containers import (
@@ -112,7 +113,7 @@ class PredictCTLearnModel(Tool):
     load_cameradirection_model_from : pathlib.Path
         Path to a Keras model file (Keras3) or directory (Keras2) for the regression
         of the primary particle arrival direction based on camera coordinate offsets.
-    load_cameradirection_model_from : pathlib.Path
+    load_skydirection_model_from : pathlib.Path
         Path to a Keras model file (Keras3) or directory (Keras2) for the regression
         of the primary particle arrival direction based on spherical coordinate offsets.
     output_path : pathlib.Path
@@ -854,6 +855,28 @@ def _create_nan_table(self, nonexample_identifiers, columns, shapes):
             )
         return nan_table
 
+    def deduplicate_first_valid(
+        self,
+        table: Table,
+        keys=('obs_id', 'event_id'),
+        valid_col='CTLearn_is_valid',
+    ):
+        """
+        Return a deduplicated Astropy Table.
+
+        For each group defined by `keys`, keep the first row where
+        `valid_col` is True. If none are valid, keep the first row.
+        """
+
+        t = table.copy()
+
+        t.sort(
+            list(keys) + [valid_col],
+            reverse=[False] * len(keys) + [True]
+        )
+
+        return unique(t, keys=list(keys), keep='first')
+
     def _store_pointing(self, all_identifiers):
         """
         Store the telescope pointing table from  to the output file.
@@ -1253,6 +1276,12 @@ def start(self):
                         classification_subarray_table[f"{self.prefix}_telescopes"] = (
                             reco_telescopes
                         )
+                # Deduplicate the subarray classification table to have only one entry per event
+                classification_subarray_table = super().deduplicate_first_valid(
+                    table=classification_subarray_table,
+                    keys=SUBARRAY_EVENT_KEYS,
+                    valid_col=f"{self.prefix}_is_valid",
+                    )
                 # Sort the subarray classification table
                 classification_subarray_table.sort(SUBARRAY_EVENT_KEYS)
                 # Save the prediction to the output file
@@ -1381,6 +1410,12 @@ def start(self):
                         energy_subarray_table[f"{self.prefix}_telescopes"] = (
                             reco_telescopes
                         )
+                # Deduplicate the subarray classification table to have only one entry per event
+                energy_subarray_table = super().deduplicate_first_valid(
+                    table=energy_subarray_table,
+                    keys=SUBARRAY_EVENT_KEYS,
+                    valid_col=f"{self.prefix}_is_valid",
+                    )
                 # Sort the subarray energy table
                 energy_subarray_table.sort(SUBARRAY_EVENT_KEYS)
                 # Save the prediction to the output file
@@ -1537,6 +1572,12 @@ def start(self):
                         direction_subarray_table[f"{self.prefix}_telescopes"] = (
                             reco_telescopes
                         )
+                # Deduplicate the subarray classification table to have only one entry per event
+                direction_subarray_table = super().deduplicate_first_valid(
+                    table=direction_subarray_table,
+                    keys=SUBARRAY_EVENT_KEYS,
+                    valid_col=f"{self.prefix}_is_valid",
+                    )
                 # Sort the subarray geometry table
                 direction_subarray_table.sort(SUBARRAY_EVENT_KEYS)
                 # Save the prediction to the output file
@@ -1717,7 +1758,7 @@ def start(self):
         self.log.info("Starting the prediction...")
         classification_feature_vectors = None
         if self.load_type_model_from is not None:
-            # Predict the energy of the primary particle
+            # Predict the classification of the primary particle
             classification_table, classification_feature_vectors = (
                 super()._predict_classification(example_identifiers)
             )
@@ -1730,7 +1771,7 @@ def start(self):
                         shapes=[(len(nonexample_identifiers),)],
                     )
                     classification_table = vstack([classification_table, nan_table])
-                # Add is_valid column to the energy table
+                # Add is_valid column to the classification table
                 classification_table.add_column(
                     ~np.isnan(
                         classification_table[f"{self.prefix}_tel_prediction"].data,
@@ -1745,6 +1786,12 @@ def start(self):
                 classification_table.rename_column(
                     f"{self.prefix}_tel_is_valid", f"{self.prefix}_is_valid"
                 )
+                # Deduplicate the subarray classification table to have only one entry per event
+                classification_table = super().deduplicate_first_valid(
+                    table=classification_table,
+                    keys=SUBARRAY_EVENT_KEYS,
+                    valid_col=f"{self.prefix}_is_valid",
+                )
                 classification_table.sort(SUBARRAY_EVENT_KEYS)
                 # Add the default values and meta data to the table
                 add_defaults_and_meta(
@@ -1793,6 +1840,12 @@ def start(self):
                 energy_table.rename_column(
                     f"{self.prefix}_tel_is_valid", f"{self.prefix}_is_valid"
                 )
+                # Deduplicate the subarray energy table to have only one entry per event
+                energy_table = super().deduplicate_first_valid(
+                    table=energy_table,
+                    keys=SUBARRAY_EVENT_KEYS,
+                    valid_col=f"{self.prefix}_is_valid",
+                )
                 energy_table.sort(SUBARRAY_EVENT_KEYS)
                 # Add the default values and meta data to the table
                 add_defaults_and_meta(
@@ -1845,6 +1898,12 @@ def start(self):
                     ~np.isnan(direction_table[f"{self.prefix}_alt"].data, dtype=bool),
                     name=f"{self.prefix}_is_valid",
                 )
+                # Deduplicate the subarray direction table to have only one entry per event
+                direction_table = super().deduplicate_first_valid(
+                    table=direction_table,
+                    keys=SUBARRAY_EVENT_KEYS,
+                    valid_col=f"{self.prefix}_is_valid",
+                )
                 direction_table.sort(SUBARRAY_EVENT_KEYS)
                 # Add the default values and meta data to the table
                 add_defaults_and_meta(