This workshop introduces Model Predictive Control (MPC) using the MPCcode software, covering both theoretical concepts and practical implementation. Participants will review key MPC principles, including predictive modeling, constraint handling, and optimization, and apply them to selected case studies. The focus will be on chemical engineering applications, though the methodology extends naturally to broader industrial automation problems. Through guided exercises, attendees will learn how to use MPCcode to modify controller architectures and internal models with simple yet useful options. Prior knowledge of MPC and Python is helpful but not required.