Alternaria blight is the most widespread and destructive disease of oilseed Brassica across the globe. In India, it is mainly caused by Alternaria brassicae (Berk.) Sacc. which infects all aboveground part of crop and produces grey color spots. Although total destruction of crop due to disease is rare, yet yield loss can reach up to 47% with reduction in seed quality viz., seed size and viability. The knowledge of probable attack of disease in advance may be very useful to farmer to take timely and appropriate protection measure to reduce the loss. Weather plays an important role in disease development. A well-tested weather-based model can be an effective tool for disease forewarning. In this study, weather-based forewarning model was developed for crop age at peak severity and maximum severity (%) of the disease on leaf and pod (used as dependent variable) for three location in India viz., New Delhi, Hisar (Haryana) and Mohanpur (West Bengal). Historical disease data (2004-14) and weather data (Temp., RH, rainfall and bright sunshine hours) were utilized as independent variable for model development and their validation for two subsequent year (2014-16). Validation of the prediction model for crop age at peak severity and maximum severity (%) of the disease proved the efficiency of the targeted forecasts. On this basis, advisory to farmers could be issued at least 2-3 week in advance with information for timely application of fungicide to manage Alternaria blight