diff --git a/models/gc_node21_baseline/utils/Node21BaselineRunner.py b/models/gc_node21_baseline/utils/Node21BaselineRunner.py
index c9ef7b31..d5c410d8 100644
--- a/models/gc_node21_baseline/utils/Node21BaselineRunner.py
+++ b/models/gc_node21_baseline/utils/Node21BaselineRunner.py
@@ -8,14 +8,14 @@
 Email:  sil.vandeleemput@radboudumc.nl
 -------------------------------------------------------------
 """
-import SimpleITK
 import json
+import sys
 from pathlib import Path
 
 from mhubio.core import Instance, InstanceData, IO, Module, Meta, ValueOutput, OutputDataCollection
 
-# Import Node21 baseline nodule detection algorithm from the node21_detection_baseline repo
-from process import Noduledetection
+
+CLI_PATH = Path(__file__).parent.absolute() / "cli.py"
 
 
 @ValueOutput.Name('noduleprob')
@@ -44,16 +44,25 @@ class Node21BaselineRunner(Module):
     @IO.OutputDatas('nodule_probs', NoduleProbability)
     @IO.OutputDatas('nodule_bounding_boxes', NoduleBoundingBox)
     def task(self, instance: Instance, in_data: InstanceData, out_data: InstanceData, nodule_probs: OutputDataCollection, nodule_bounding_boxes: OutputDataCollection) -> None:
-        # Read input image
-        input_image = SimpleITK.ReadImage(in_data.abspath)
-
-        # Run nodule detection algorithm on the input image and generate predictions
-        tmp_path = Path("/app/tmp")
-        predictions = Noduledetection(input_dir=tmp_path, output_dir=tmp_path).predict(input_image=input_image)
-
-        # Export the predictions to a JSON file
-        with open(out_data.abspath, "w") as f:
-            json.dump(predictions, f, indent=4)
+        # build command (order matters!)
+        cmd = [
+            sys.executable,
+            str(CLI_PATH),
+            in_data.abspath,
+            out_data.abspath
+        ]
+
+        # run the command as subprocess
+        self.subprocess(cmd, text=True)
+
+        # Confirm the expected output file was generated
+        if not Path(out_data.abspath).is_file():
+            raise FileNotFoundError(f"Node21BaseLineRunner - Could not find the expected "
+                                    f"output file: {out_data.abspath}, something went wrong running the CLI.")
+
+        # Read the predictions to a JSON file
+        with open(out_data.abspath, "r") as f:
+            predictions = json.load(f)
 
         # Export the relevant data
         for nodule_idx, box in enumerate(predictions["boxes"]):
diff --git a/models/gc_node21_baseline/utils/cli.py b/models/gc_node21_baseline/utils/cli.py
new file mode 100644
index 00000000..920a99cc
--- /dev/null
+++ b/models/gc_node21_baseline/utils/cli.py
@@ -0,0 +1,50 @@
+"""
+---------------------------------------------------
+Mhub / DIAG - CLI for the Node21 baseline Algorithm
+  The model algorith was wrapped in a CLI to ensure
+  the mhub framework is able to properly capture
+  the stdout generated by the algorithm
+---------------------------------------------------
+
+---------------------------------------------------
+Author: Sil van de Leemput
+Email:  sil.vandeleemput@radboudumc.nl
+---------------------------------------------------
+"""
+
+import argparse
+from pathlib import Path
+import json
+
+import SimpleITK
+
+# Import Node21 baseline nodule detection algorithm from the node21_detection_baseline repo
+from process import Noduledetection
+
+
+def run_classifier(input_cxr: Path, output_json_file: Path):
+        # Read input image
+        input_image = SimpleITK.ReadImage(str(input_cxr))
+
+        # Run nodule detection algorithm on the input image and generate predictions
+        tmp_path = Path("/app/tmp")
+        predictions = Noduledetection(input_dir=tmp_path, output_dir=tmp_path).predict(input_image=input_image)
+
+        # Export the predictions to a JSON file
+        with open(output_json_file, "w") as f:
+            json.dump(predictions, f, indent=4)
+
+
+def run_classifier_cli():
+    parser = argparse.ArgumentParser("CLI to run the Node21 baseline classifier")
+    parser.add_argument("input_cxr", type=str, help="input CXR image (MHA)")
+    parser.add_argument("output_json_file", type=str, help="Output nodule bounding boxes and probabilities predictions (JSON)")
+    args = parser.parse_args()
+    run_classifier(
+        input_cxr=Path(args.input_cxr),
+        output_json_file=Path(args.output_json_file)
+    )
+
+
+if __name__ == "__main__":
+    run_classifier_cli()