Index of Industrial Production (IIP) data is one of the important economic indicators that track the manufacturing activity of different sectors of an economy. In this paper, an attempt is made to forecast the IIP data using traditional and deep learning statistical approaches. The data from Apr-2012 to Feb-2020 is used for forecasting. The appropriate best model is evaluated by comparing mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE). The results of the study show that RNN is performing better than the other models i.e ARIMA (Traditional method), FFNN, and LSTM (ANN models). Therefore RNN model is used for forecasting. The forecasted values from Mar-2020 to Jun-2021 are compared with the actual IIP values and resulted in a clear decline in industrial production because of lockdown.