The Collision Avoidance and Navigation System using Automatic Identification System (AIS) aims to enhance maritime safety by leveraging AIS technology. AIS provides real-time vessel information such as position, course, speed, and identification, which can be utilized to develop an intelligent system for collision avoidance and navigation in busy maritime environments. This research proposes a comprehensive system integrating AIS data with advanced algorithms and decision-making techniques to predict collision risks and aid in safe navigation. The system utilizes historical AIS data to analyze patterns and identify potential collision scenarios based on factors such as vessel proximity, course convergence, and relative speed. By employing machine learning and data analytics, the system can generate a Collision Risk Index (CRI) for each vessel, indicating the level of collision risk it may face. This information can be used to provide early warnings and recommendations to ship operators, allowing them to take proactive measures to avoid collisions. Additionally, the system incorporates intelligent routing algorithms that consider the predicted collision risks to suggest safer and more efficient vessel navigation paths. By considering real-time AIS data, weather conditions, and traffic density, the system can optimize vessel routes to minimize collision risks and improve overall maritime safety. The proposed Collision Avoidance and Navigation System using AIS holds significant potential to enhance safety in busy maritime environments. By leveraging AIS data and advanced algorithms, it enables proactive collision avoidance and intelligent routing decisions, reducing the likelihood of collisions and improving the efficiency of vessel navigation. Further research and development are required to validate and optimize the system’s performance in real-world scenarios.