A disease predictive model for Potato leaf roll virus (PLRV) was developed based on a ten year dataset of disease incidence and environmental variables and validated by two years data collected in Faisalabad, Pakistan. Maximum and minimum air temperatures, relative humidity and rainfall were employed as independent variables while PLRV disease incidence served as the response variable. Stepwise regression analysis was performed to select potentially useful predictor variables for model development. In stepwise regression analysis minimum temperature, relative humidity and rainfall emerged as the main contributing environmental variables for disease development. The model performance was evaluated based on coefficient of determination (R ) and the comparison of observed and predicted disease incidence. Model so developed explained 70% of the variability in disease development and when validated on an independent dataset, the model explained 67.5% of the variability in disease incidence. This prediction model can be used for the management of PLRV in this region.