diff --git a/commenting_code_model/encode_model.py b/commenting_code_model/encode_model.py
new file mode 100644
index 0000000..90f7e17
--- /dev/null
+++ b/commenting_code_model/encode_model.py
@@ -0,0 +1,79 @@
+indent_prefix = 2 * ' '
+
+
+def indent_line(line):
+    return indent_prefix + line
+
+
+def encode_branch(branch):
+    if isinstance(branch, dict):
+        return encode_tree(branch)
+    elif isinstance(branch, (int, float)):
+        return [ indent_line('return {};'.format(branch)) ]
+    else:
+        return [ indent_line('return "{}";'.format(branch)) ]
+
+# if value at index is smaller than threshold
+# enter left, else right
+
+
+def encode_tree(tree):
+    lines = [
+        "print(\"Considering feature {index}, is it smaller than {threshold}?\");".format(index=tree['index'], threshold=tree['value']),
+        "// timeout code",
+        "if (r[{index}] < {threshold}) {{".format(index=tree['index'], threshold=tree['value']),
+        indent_line("print(\"Yes\");"),
+        *encode_branch(tree['left']),
+        "}",
+        "else {",
+        indent_line("print(\"No\");"),
+        *encode_branch(tree['right']),
+        "}"
+    ]
+
+    return map(indent_line, lines)
+
+
+def make_classifier (tree):
+  lines = [
+    "char predict(float *r) {",
+    *encode_tree(tree),
+    "}"
+  ]
+
+  return('\n'.join(lines))
+
+if __name__ == '__main__':
+  import json
+  import os.path
+  import glob
+  basepath = os.path.dirname(os.path.realpath(__file__))
+  globpath = os.path.realpath(os.path.join(basepath, 'random_forest_model_*-trees.json'))
+  
+  models = glob.glob(globpath)
+
+  # Search for exported models
+  print("Found:")
+  for k, modelpath in enumerate(models):
+    print("[{}] {}".format(k, modelpath))
+
+  model_key = int(input("Which model?\n"))
+
+  modelpath = models[model_key]
+
+  # Open model
+  with open(modelpath, 'r') as file_in:
+    # Parse the forest
+    forest = json.load(file_in)
+    modelname, _ = os.path.splitext(os.path.basename(modelpath))
+    classifiernamepattern = 'classifier_{}_tree_{{}}.h'.format(modelname)
+
+    # Walk through the forest and visualize the trees
+    for idx, tree in enumerate(forest):
+      print('Transforming tree {} of {}'.format(idx, len(forest)))
+      code = make_classifier(tree)
+
+      with open(os.path.join(basepath, classifiernamepattern.format(idx)), 'w') as h:
+        h.write(code)
+    
+  print('Classifiers placed in: {}'.format(basepath))
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