This paper focuses on the fluid catalytic cracking (FCC) process and reviews recent developments in its modeling, monitoring, control, and optimization. This challenging process exhibits complex behavior, requiring detailed models to express the nonlinear effects and extensive interactions between input and control variables that are observed in industrial practice. The FCC models currently available differ enormously in terms of their scope, level of detail, modeling hypothesis, and solution approaches used. Nevertheless, significant benefits from their effective use in various routine tasks are starting to be widely recognized by the industry. To help improve the existing modeling approaches, this review describes and compares the different mathematical frameworks that have been applied in the modeling, simulation, control, and optimization of this key downstream unit. Given the effects that perturbations in the feedstock quality and other unit disturbances might have, especially when associated with frequent changes in market demand, this paper also demonstrates the importance of understanding the nonlinear behavior of the FCC process. The incentives associated with the use of advanced model-based supervision strategies, such as nonlinear model predictive control and real-time optimization techniques, are also presented and discussed.