diff --git a/benchmark/Experiments.py b/benchmark/Experiments.py
index 3696ffe..6865f98 100644
--- a/benchmark/Experiments.py
+++ b/benchmark/Experiments.py
@@ -227,14 +227,11 @@ class Experiment:
                 if not self.ignore_nan:
                     print(res["test_score"])
                     raise ValueError("NaN in results")
-                results = []
-                for item in res["test_score"]:
-                    if not np.isnan(item):
-                        results.append(item)
+                results = res["test_score"][~np.isnan(res["test_score"])]
             else:
                 results = res["test_score"]
-            self.scores.append(results)
-            self.times.append(res["fit_time"])
+            self.scores.extend(results)
+            self.times.extend(res["fit_time"])
             for result_item in res["estimator"]:
                 nodes_item, leaves_item, depth_item = Models.get_complexity(
                     self.model_name, result_item
diff --git a/benchmark/Models.py b/benchmark/Models.py
index 68df171..8c03ae1 100644
--- a/benchmark/Models.py
+++ b/benchmark/Models.py
@@ -15,6 +15,19 @@ from xgboost import XGBClassifier
 import sklearn
 import xgboost
 
+import random
+
+
+class MockModel(SVC):
+    # Only used for testing
+    def predict(self, X):
+        if random.random() < 0.1:
+            return [float("NaN")] * len(X)
+        return super().predict(X)
+
+    def nodes_leaves(self):
+        return 0, 0
+
 
 class Models:
     @staticmethod
@@ -50,6 +63,7 @@ class Models:
             ),
             "GBC": GradientBoostingClassifier(random_state=random_state),
             "RandomForest": RandomForestClassifier(random_state=random_state),
+            "Mock": MockModel(random_state=random_state),
         }
 
     @staticmethod
diff --git a/benchmark/tests/Experiment_test.py b/benchmark/tests/Experiment_test.py
index 722052b..7ef9ff7 100644
--- a/benchmark/tests/Experiment_test.py
+++ b/benchmark/tests/Experiment_test.py
@@ -1,4 +1,6 @@
 import json
+from io import StringIO
+from unittest.mock import patch
 from .TestBase import TestBase
 from ..Experiments import Experiment
 from ..Datasets import Datasets
@@ -8,7 +10,9 @@ class ExperimentTest(TestBase):
     def setUp(self):
         self.exp = self.build_exp()
 
-    def build_exp(self, hyperparams=False, grid=False, model="STree"):
+    def build_exp(
+        self, hyperparams=False, grid=False, model="STree", ignore_nan=False
+    ):
         params = {
             "score_name": "accuracy",
             "model_name": model,
@@ -21,7 +25,7 @@ class ExperimentTest(TestBase):
             "title": "Test",
             "progress_bar": False,
             "folds": 2,
-            "ignore_nan": False,
+            "ignore_nan": ignore_nan,
         }
         return Experiment(**params)
 
@@ -157,3 +161,15 @@ class ExperimentTest(TestBase):
             self.assertEqual(computed["state_names"][key], value)
         for feature in expected["features"]:
             self.assertIn(feature, computed["features"])
+
+    @patch("sys.stdout", new_callable=StringIO)
+    def test_experiment_with_nan_not_ignored(self, mock_output):
+        exp = self.build_exp(model="Mock")
+        self.assertRaises(ValueError, exp.do_experiment)
+        output_text = mock_output.getvalue().splitlines()
+        expected = "[      nan 0.8974359]"
+        self.assertEqual(expected, output_text[0])
+
+    def test_experiment_with_nan_ignored(self):
+        self.exp = self.build_exp(model="Mock", ignore_nan=True)
+        self.exp.do_experiment()