Cellular Automata (CA) models have been extensively utilized to simulate and understand crowd dynamics and pedestrian movement. This comprehensive review encompasses key papers that have significantly contributed to the development and application of CA models in crowd movement studies. The review highlights the diverse perspectives and applications of CA, including fuzzy cellular automata, virtual fields cellular automata, and hardware implementations. Key areas of focus include pedestrian dynamics in everyday scenarios and emergency evacuations, integrating various factors such as speed, direction, neighboring cell influence, and environmental obstacles. The CA models’ ability to discretize space and time allows for detailed simulation of individual movements and interactions, generating emergent behaviors that closely mimic real-life crowd dynamics. Furthermore, advancements in computational power, such as parallel computing and GPU acceleration, have enabled more sophisticated and faster simulations, enhancing the applicability of CA models in urban planning, public space design, and emergency awareness. This review underscores the importance of continuous refinement of CA models and the integration of interdisciplinary approaches to improve our understanding of pedestrian behavior and the safety and efficiency of crowded environments.