Abstract: The disclosed embodiments illustrate methods of data processing for real-time prediction of crowdedness in vehicles in transit. The method includes receiving a current location of a vehicle, a real-time traffic information along a route of transit, and a current passenger demand at a first subsequent station and a second subsequent station. The method includes predicting a dwell time for the vehicle corresponding to the first subsequent station. The method includes predicting an arrival time instant of the vehicle at the second subsequent station based on a predicted first travel time of the vehicle, a predicted second travel time of the vehicle, and the predicted dwell time. The method includes predicting a passenger occupancy of the vehicle at the predicted arrival time instant at the second subsequent station based on at least a first passenger demand, a second passenger demand associated with the second subsequent station, and a passenger alighting pattern.