A methodology was developed for large area yield forecast using a crop simulation model and a discrete technology trend, and was applied to the coherent wheat yield variability zones of Eastern Uttar Pradesh, India. The approach consisted of three major steps: (a) prediction of technology trend yield using historical yield series of the region; (b) prediction of weather-induced deviation in wheat yield using CERES-Wheat simulation model and relating weather-induced deviation in simulated yield to deviation in observed yield deviations from technology trend; and (c) final yield forecast by incorporating predicted yield deviation in trend predicted yield. The regression coefficients for step (b) were generated using 10 years' data (1984/85–1994/95) and the reliability of the approach was tested on a data set of 5 years' independent data (1995/96–1999/2000). The results showed that this approach could capture year-to-year variability in large area wheat yield with reasonable accuracy. The Root Mean Square Error (RMSE) between observed and predicted yield was reported as 0·098 t/ha for the mean yield of 2·072 t/ha (4·72%). However, the RMSE was slightly higher in the forecasting period in comparison to the calibration period. The use of this methodology for issuing the pre-harvest forecast and the effect of upgrading the technology trend were also studied. The pre-harvest forecasts were made using in-season weather data up to the end of February and climatic-normal for the rest of the wheat-growing season, which showed good agreement with observed wheat yields. The forecasts of wheat yield for the season 1999/2000 were made using the technology trend up to 1994/95 and the updated technology trend up to 1998/99, which showed that the RMSE fell in the latter case, from 4·10 to 2·50%.