diff --git a/Task 4/prediction.py b/Task 4/prediction.py
new file mode 100644
index 0000000..5151d08
--- /dev/null
+++ b/Task 4/prediction.py	
@@ -0,0 +1,54 @@
+from keras.models import model_from_json
+import operator
+import cv2
+
+json_file = open("model-bw.json", "r")
+model_json = json_file.read()
+json_file.close()
+loaded_model = model_from_json(model_json)
+loaded_model.load_weights("model-bw.h5")
+print("Loaded model from disk")
+
+cap = cv2.VideoCapture(0) 
+
+categories = {0: 'ZERO', 1: 'ONE', 2: 'TWO', 3: 'THREE', 4: 'FOUR', 5: 'FIVE'}
+
+while True:
+    _, frame = cap.read()
+    frame = cv2.flip(frame, 1)
+
+    x1 = int(0.5*frame.shape[1])
+    y1 = 10
+    x2 = frame.shape[1]-10
+    y2 = int(0.5*frame.shape[1])
+
+    cv2.putText(frame, "Expressando - TDOC 2021", (175, 450), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (225,255,0), 3)
+    cv2.rectangle(frame, (x1-1, y1-1), (x2+1, y2+1), (255,255,255) ,3)
+    roi = frame[y1:y2, x1:x2]
+
+    roi = cv2.resize(roi, (64, 64)) 
+    roi = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
+    cv2.putText(frame, "R.O.I", (440, 350), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0,225,0), 3)
+
+    _, test_image = cv2.threshold(roi, 120, 255, cv2.THRESH_BINARY)
+    cv2.imshow("ROI", test_image)
+
+    result = loaded_model.predict(test_image.reshape(1, 64, 64, 1))
+    prediction = {'ZERO': result[0][0], 
+                  'ONE': result[0][1], 
+                  'TWO': result[0][2],
+                  'THREE': result[0][3],
+                  'FOUR': result[0][4],
+                  'FIVE': result[0][5]} 
+    prediction = sorted(prediction.items(), key=operator.itemgetter(1), reverse=True) #(0.9 = FIVE, 0.7, 0.6, 0.5, 0.4)
+    cv2.putText(frame, "PREDICTION:", (30, 90), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255), 2)
+    cv2.putText(frame, prediction[0][0], (80, 130), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255), 2)    
+    cv2.imshow("Frame", frame)
+
+    interrupt = cv2.waitKey(10)
+    if interrupt & 0xFF == 27:
+        break
+
+
+cap.release()
+cv2.destroyAllWindows()