Expert systems are a branch of artificial intelligence that utilizes specialized knowledge to solve problems at the level of an expert. In the field of agriculture, expert systems are used for diagnosing plant diseases. In this research, an expert system was designed and developed with the aim of assisting pineapple farmers in determining the diagnosis of diseases based on the main symptoms observed in the plants. To overcome knowledge uncertainty, the Bayesian probability method was employed in this expert system. The diagnostic process begins with a consultation session, where the system asks relevant questions to the farmers based on the observed symptoms in the pineapple plants. The ultimate outcome of this study is an expert system capable of diagnosing diseases in pineapple plants and providing effective solutions with an accuracy rate of 93.34%. Additionally, the system provides probability values for each diagnosed disease, indicating the system's confidence level in the identified diseases, and offers treatment recommendations or solutions to the pineapple farmers.