The objective of this work was to predict the probability of outbreak of late blight and early blight epiphytotic diseases through weather patterns during the potato harvest season.Future meteorological data for the years 2024 to 2075 obtained from the National Institute of Meteorology in Cuba were used. For the development of the forecasting model, disease behavior rules were defined and, specifically for early blight, the phenological age of the crop was also considered as a function of thermal variables (P-Days). The web system was implemented using the Python programming language, the Flask and Bootstrap frameworks, and the necessary libraries, and PyCharm as the development environment. Likewise, the PostgreSQL manager and PgAdmin were used for data management and as a tool for information administration. A web system was obtained that alerts on the probability of outbreak of late blight and early blight in the provinces of Mayabeque, Villa Clara and Ciego de Avila, important potato-producing regions in Cuba. The prognosis for the years 2025, 2030 and 2035 were analyzed and it was found that the Mayabeque region presents a higher incidence of both diseases and the month of January is more prone to the proliferation of the phytopathogen. The web system is an intelligent tool to guide farmers in making the necessary decisions and prevent an epidemic outbreak

https://doi.org/10.1016/j.atech.2025.101003