This paper investigates the best possible forecasting price models for three important agricultural products in Bangladesh namely potato, onion and garlic using time-series and secondary data from January 2000 to December 2014. The main objective of this paper is to find out the appropriate time series models using some of the latest selection criteria that could describe the best price patterns of the above mentioned three crops. To forecast the prices of the crops, the ARIMA models were used, based on model selection criteria and error statistics among the competing models. The overall findings of the study indicate that the fitted models are satisfactory for the respective commodities. The study observed increasing trends in forecasted prices of all three commodities. In particular, the increase in the price of garlic has been observed to be very high compared to that of potato and onion. The study also found that the best fitted SARIMA model for potato is SARIMA (1,0,0) (0,1,2)12, for onion SARIMA (2,0,0) (0,1,1)12, and for garlic SARIMA (2,1,3) (0,1,3)12.