AbstractArtificial Neural Network (ANN) provides an attractive alternative tool for researchers for agricultural forecasting. The Multi Layer Feed Forward Neural Net (MLFFNN) is one of the most widely used neural nets. Here, the MLFFNN architecture is examined and compared with time series models such as Autoregressive Integrated Moving Average (ARIMA) model for prediction of agricultural production. Both models were compared using visualization technique and statistical tests and the results were illustrated numerically and graphically.