This research pertains to the design of a Machine Learning based PID control is an optimal control strategy for high-temperature-short-time (HTST) pasteurization process. Its performance is evaluated against the classical Proportional Integral Derivative (PID) controller. Manual tuning of the PID controller is a tedious task. To cut back the aforesaid problem, Machine Learning based PIDs were simulated for controlling the temperature in the HTST process. A novel hybrid Combined Feedforward-Feedback control Data Driven control based PID control in introducing to improve the process performance. (FF-FB-DDCPID)