Epilepsy, or apoplexy, is a chronic disease characterized by recurrent seizures and impaired consciousness due to disorders of the central nervous system. In developing countries, including in RSU Putri Bidadari, epilepsy management is often hampered by high consultation costs, resulting in suboptimal quality of treatment and patient recovery. To overcome this challenge, a system is needed that can facilitate the diagnosis and treatment of epilepsy more efficiently. By using this method, RSU Putri Bidadari can improve the precision of epilepsy diagnosis and determine more appropriate treatment steps, despite limited resources. The Bayes method, as a statistical approach, offers a potential solution to improve the accuracy of diagnosis through data-based probability estimation of diseases and symptoms reported by patients such as frequent hunger, thirst, urination, weight loss, vaginal infections, easy fatigue, tingling legs, and blurred vision. The analysis results of the system show an estimated probability of 73% for patients suffering from generalized epilepsy. The Bayes method-based system is expected to help RSU Putri Bidadari in providing more effective treatment and improving the overall quality of life of epilepsy patients.