This study explores the crash astern maneuver, a critical emergency maneuver used to rapidly halt a vessel’s forward momentum to avoid collisions or grounding. The paper examines the mechanical aspects of the maneuver, the impact of Maximum Continuous Rating (MCR) reduction on stopping distances, and the role of engine control systems in ensuring effective deceleration. Key findings reveal that reducing MCR leads to longer stopping times, though the corresponding reduction in speed may counterbalance the diminished thrust capacity of the engine. The research further investigates alternative stopping methods, such as rudder low-frequency cycling, water injection, and dynamic positioning, each providing significant contributions to deceleration under specific operational conditions. The study also highlights the risks associated with cavitation and mechanical stresses during rapid engine reversals and emphasizes the importance of precise RPM management. Additionally, the integration of Artificial Intelligence (AI) in crash astern maneuvers is proposed to enhance decision-making, optimize engine thrust management, and improve overall maneuvering efficiency. AI systems that incorporate real-time data, machine learning algorithms, and decision support tools are identified as crucial for ensuring safe and efficient emergency operations. The paper concludes with recommendations for improving maneuvering systems, including the use of automation, advanced simulation tools, and AI to support more effective crash astern responses, ensuring enhanced safety and operational efficiency in maritime emergency.