Aphids are becoming the major insect pest affecting wheat productivity in major wheat growing areas of South Asia, Latin America and Africa. Forecasting the incidence and severity of aphids is expected to significantly help in their management. Here, a set of weather based models were developed which predict the timing and severity of aphid infestation at Ludhiana

(30.9010° N, 75.8573° E) falling under North Western Plain Zone (NWPZ) and at Niphad (20.0800° N, 74.1093° E) in the Peninsular Zone (PZ) of India. The NWPZ is the most important wheat growing zone of India contributing about 90% of the national buffer stock of wheat grains. The corn leaf aphid, Rophalosiphum maidis (Fitch) is the pre-dominant species at Ludhiana, whereas, Rophalosiphum padi (Linnaeus) at Niphad. The aphid population and weather data collected over eight years (2006-07 to 2013-14) at these two locations were used, while the prediction power of models were successfully validated over three subsequent seasons (2014-15, 2015-16 and 2016-17). The developed models can to predict the crop’s age - when aphids first colonize the plants, when the aphid population attains the peak along with informing about the peak intensity of the aphid population. For predicting the crop’s age at first appearance of aphids at Ludhiana, the weighted interaction of the relative humidity (RH) in the morning and the number of hours of sunshine (NHS) were found to be the key parameters, whereas at Niphad, the weighted NHS and the interaction between RH (evening) and the NHS were the important predictive parameters. For predicting the crop’s age at which population peaked at Ludhiana, the weighted interaction of RH (evening) and the NHS along with the weighted interaction of minimum temperature and RH (morning) were important parameters, whereas at Niphad, the weighted NHS and the interaction of RH (morning & evening) were important. Likewise, for predicting the maximum aphid population at Ludhiana, the weighted interaction of minimum temperature and RH (morning) were important, while at Niphad, the key parameters were the weighted interaction of RH (evening) with the NHS. The developed models are expected to facilitate the aphid management through a quite accurate forecasting in the locations studied.