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Road traffic congestions continue to remain a major problem in most of the cities around the world resulting in massive delays, increased fuel wastage and monetary losses. Traffic congestions can occur due to poorly planned road networks, poor traffic management in critical hotspots of the city, bad weather conditions or due to an increase in the volume of vehicles. The traffic data in smart cities can easily be obtained with the help of sensors. A machine learning model would help us in predicting the traffic congestion in advance by providing the appropriate data to the model. The machine learning algorithm used to predict the traffic congestion is Random Forest Algorithm due to its high accuracy and robustness.