The tomato industry plays a crucial role in the agricultural sector, necessitating accurate supply and demand forecasting to aid farmers and stakeholders in making informed decisions. This study aimed to design and develop TomatoCare, a forecasting system that leverages ARIMA (AutoRegressive Integrated Moving Average) modeling to provide reliable forecasts and valuable insights for effective resource allocation and market planning. The research followed a mixed-methods approach, combining various data collection methods such as interviews with Subject Matter Experts (SMEs), data scraping, and data mining from external sources, including the Department of Agriculture, Department of Trade and Industry, and Philippine Statistics Authority websites. These methods facilitated the collection of comprehensive and up-to-date data on tomato supply and demand.