In process industries, liquid level control in tanks and flow regulation between interconnected tanks are fundamental yet challenging tasks due to the complexity and dynamic nature of such systems. This paper addresses the need for effective control strategies by comparing the performance of a Model Predictive Controller (MPC) with that of a conventional Proportional-Integral-Derivative (PID) controller in a coupled tank system. MPC has gained significant attention over the past two decades, particularly in the chemical, petrochemical, and metallurgical sectors, due to its ability to handle multivariable systems and incorporate system constraints. In this study, both controllers are implemented to maintain the desired liquid level, and their performances are evaluated using key time-domain metrics, including overshoot and settling time, as well as various performance indices. Simulation results demonstrate that MPC significantly outperforms the PID controller, offering superior dynamic response and robustness under varying operating conditions.