Wheat is a dominant product in the consumption basket of Indian households and can be considered as a strategic commodity. In this paper different ARIMA time series models were specified and estimated. Forecasting performance of these models were evaluated and compared by using common criteria such as: root mean square error, mean absolute deviation and mean absolute percentage error. The data used in this study include wholesale prices of wheat for year 2002 to 2012. Empirical results showed that ARIMA (1,1,1) price forecast time series model fitted the price series well and they have correctly predicted the future trend of the price series within the sample period of the study. Thus, ARIMA (1,1,1) was the most representative model for the price forecast of wheat in Sriganganagar market of Rajasthan. This model can facilitate the farmers and wholesalers in effective decision making.