Agriculture is the backbone of a country’s economy, providing food, fiber, crops, and livestock while creating jobs and reducing poverty. Agriculture is crucial in Morocco’s Souss-Massa region, particularly in citrus fruit production. This project focuses on detecting citrus diseases and providing phytosanitary recommendations using image processing techniques integrated into a web platform developed with the Streamlit framework. Identifying citrus diseases is essential for growers to prevent annual losses. The simulation results show that the network classifier delivers minimal error during training and achieves high classification accuracy. This model is designed to assist farmers in detecting diseases in orange and lemon plants, enabling timely and appropriate treatment.