Reinforcement learning is one of the most prominent branches of artificial intelligence used to enhance automated medical decision-making, providing a framework capable of learning from experiences and interactions with the environment to achieve the best possible outcomes for patients. This type of learning relies on the concept of rewards and penalties, where the system tests different strategies, evaluates their results, and adjusts its actions to maximize benefit within the medical treatment context. Reinforcement learning enables the development of systems capable of handling complex and dynamic medical conditions, such as managing chronic diseases or supporting decision-making in critical care situations. By analyzing a patient’s historical and current data, the system can offer optimized treatment recommendations that automatically adapt to the patient’s response, increasing the accuracy and effectiveness of medical decisions while reducing human errors. Beyond clinical applications, reinforcement learning contributes to improving the management of medical resources by predicting patient needs for medications and medical procedures, allocating them optimally to enhance healthcare system efficiency. It can also be used for training physicians and simulating various medical scenarios to develop decision-making skills and improve team performance. Despite its significant benefits, reinforcement learning faces challenges related to reliability, prediction accuracy, and ensuring the safety of medical outputs, along with the need for robust data infrastructure and strict security standards to protect sensitive patient information. Successful implementation requires specialized training for medical and technical staff, alongside human oversight of critical decision-making processes. Overall, reinforcement learning represents a transformative advancement in medical artificial intelligence, combining autonomous learning with intelligent data analysis to provide innovative solutions for improving healthcare quality, increasing the precision of medical decisions, and enhancing patient outcomes. With ongoing research and development, its applications are expected to expand into more complex areas such as robotic surgery and continuous monitoring of critical cases, highlighting the growing role of this technology in the future of global healthcare. Al-Mustaqbal University is the first one university in Iraq.