diff --git a/src/python/nimbusml/pipeline.py b/src/python/nimbusml/pipeline.py
index 8a2d88af..3323f646 100644
--- a/src/python/nimbusml/pipeline.py
+++ b/src/python/nimbusml/pipeline.py
@@ -2073,13 +2073,9 @@ def _predict(self, X, y=None,
                 isinstance(X, DataFrame) and isinstance(y, (str, tuple))):
             y = y_temp
 
-        is_transformer_chain = False
-        with ZipFile(self.model) as model_zip:
-            is_transformer_chain = any('TransformerChain' in item
-                                   for item in model_zip.namelist())
-
         all_nodes = []
-        if is_transformer_chain:
+        if (hasattr(self, '_is_transformer_chain') and
+            self._is_transformer_chain):
             inputs = dict([('data', ''), ('transform_model', self.model)])
             if isinstance(X, FileDataStream):
                 importtext_node = data_customtextloader(
@@ -2171,10 +2167,12 @@ def _predict(self, X, y=None,
             self._run_time = time.time() - start_time
             raise e
 
-        if is_transformer_chain:
+        if (hasattr(self, '_is_transformer_chain')
+            and self._is_transformer_chain
+            and hasattr(out_data, 'PredictedLabel')
+            and out_data.PredictedLabel.dtype == 'bool'):
             out_data['PredictedLabel'] = out_data['PredictedLabel']*1
 
-
         if y is not None:
             # We need to fix the schema for ranking metrics
             if evaltype == 'ranking':
@@ -2617,6 +2615,10 @@ def load_model(self, src):
         self.model = src
         self.steps = []
 
+        with ZipFile(self.model) as model_zip:
+            self._is_transformer_chain = any('TransformerChain' in item
+                                             for item in model_zip.namelist())
+
     def __getstate__(self):
         odict = {'export_version': 2}
 
diff --git a/src/python/nimbusml/tests/pipeline/test_load_save.py b/src/python/nimbusml/tests/pipeline/test_load_save.py
index 3807507e..9bb29a14 100644
--- a/src/python/nimbusml/tests/pipeline/test_load_save.py
+++ b/src/python/nimbusml/tests/pipeline/test_load_save.py
@@ -11,7 +11,7 @@
 import numpy as np
 import pandas as pd
 
-from nimbusml import Pipeline
+from nimbusml import FileDataStream, Pipeline
 from nimbusml.datasets import get_dataset
 from nimbusml.feature_extraction.categorical import OneHotVectorizer
 from nimbusml.linear_model import FastLinearBinaryClassifier, OnlineGradientDescentRegressor
@@ -33,6 +33,8 @@
 (train, label) = get_X_y(train_file, label_column, sep=',')
 (test, test_label) = get_X_y(test_file, label_column, sep=',')
 
+mlnet_model = os.path.join(os.path.dirname(__file__), '..', 'utils', 'models', 'UciAdultMlNetModel.zip')
+
 def get_temp_file(suffix=None):
     fd, file_name = tempfile.mkstemp(suffix=suffix)
     fl = os.fdopen(fd, 'w')
@@ -148,6 +150,12 @@ def test_model_datastream(self):
 
         os.remove(model_filename)
 
+    def test_mlnet_model_can_be_scored(self):
+        data = FileDataStream.read_csv(test_file, sep=',', numeric_dtype=np.float32)
+        model = Pipeline()
+        model.load_model(mlnet_model)
+        model.predict(data)
+
     def test_pipeline_saves_complete_model_file_when_pickled(self):
         model_nimbusml = Pipeline(
             steps=[
diff --git a/src/python/nimbusml/tests/utils/models/UciAdultMlNetModel.zip b/src/python/nimbusml/tests/utils/models/UciAdultMlNetModel.zip
new file mode 100644
index 00000000..6bb4318c
Binary files /dev/null and b/src/python/nimbusml/tests/utils/models/UciAdultMlNetModel.zip differ