The time series data of Aus rice area and production of Bangladesh for the periods 1971-1972 to 2013-2014, collected from ‘Year Book of Agricultural Statistics’ is published by Bangladesh Bureau of Statistics (BBS), Bangladesh, used in this study. Time series model: In this study the methodology first refers to use of ARIMA model as propounded by Box-Jenkins for forecasting of Aus rice area and production in Bangladesh. The Box-Jenkins methodology refers to the set of procedures for identifying, fitting, and checking models with time series data. (1) A pth-order autoregressive model: AR(p), which has the general form- Yt = Ø0 +C1Yt-1 +Ø2Ut-2 + ... +Øj pYt- p + e t, where,Yt = Response (dependent) variable at time t, Yt-1, Yt-2 ,..., Yt- p = Response variable at time, lags t−1, t−2, . . . , t−p, respectively. Ø0, Ø1, Ø2 ,..., Ø p = Coefficients to be estimated, € t = Error term at time t. (2) A qth-order moving average model: MA(q), which has the general form- Yt = µ + €t -ø1€t-1 -ø2€t-2 - ... -øq€t-q, where, Yt = Response (dependent) variable at time t, µ = Constant mean of the process, ø1,ø 2,...,øq = Coefficients to be estimated, €t -1, €t -2 ,...,€t -q = Errors in previous time periods that are incorporated in the response Yt, €t = Error term at time t, (3) Autoregressive Integrated Moving Average Model: ARIMA (p,d,q), which has the general form Yt = Ø0 + Ø1Yt -1 + Ø2Yt -2 + ... + ØpYt - p + €t -Ø1€t-1 -Ø2€t-2 - ... -Øq€t-q, where, p, q and d denote the autoregressive, moving average and differenced order parameter of the process, respectively. Jarque-Bera test: The normality assumption is defined here using Jarque-Bera (1987) test,which a goodness of fit measure of departure from normality, based on the sample kurtosis (k) and skewness (s). Box-Pierce Q test: In order to check the adequacy of the model using a chi-square test, known as the Box-Pierce Q statistic, (Box and Pierce, 1970) on the autocorrelations of the residuals, the test statistic Q is defined.