Through an integration of seasonal climate forecasts (SCF) and rice pest epidemiological models, a potential risk forrice pest epidemics can be predicted even before a cropping season starts. The objective of the study was to developand evaluate an epidemiological “rtdSim” model for tungro, a vector-born rice disease, aiming at predicting a seasonaltungro risk in the Bicol Region of the Philippines. Predicting tungro epidemics requires many components explaining thecomplex nature of the three-cornered pathosystems (virus, vector, and host) and their interactions with environmental variables.The rtdSim model successfully calculated number of rice hills infected with the rice tungro virus through its vector, thegreen leafhopper (GLH). The present study highlights the potential for developing a climate-based early warning systemfor rice pests, thus allowing better decision-making on a seasonal level.