The paper investigates the best possible forecasting price models for three important agricultural products of Bangladesh namely potato, onion and garlic based on time-series based 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 latest selection criteria that could describe the best price patterns of the above mentioned three agricultural items. In order to forecast the prices of the items, 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 respective commodities. The study finds increasing trends in forecasted prices of all three commodities. In particular, the increase in price of garlic has been observed to be very high compared to potato and onion. The study also finds 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.