Indian monsoon rainfall is an extremely important affair in socio-economic well-being of the country. Recently, climatic changes have introduced significant uncertainty and irregularity in the Indian Summer Monsoon (ISM) cycle. Such unpredictability has been evidenced in all the elements of monsoon, e.g., onset, intensity, and regularity. Rain amount has been the eye of all predictions for obvious reasons. But, in the recent scenario, other components of the monsoon process have also become extremely crucial to be forecasted. The current work has regionalized Indian subcontinent using a rough-fuzzy c-means algorithm and proposed five updated monsoon zones. Four deep learning networks using Bi-LSTM architecture for four of the resulting regions have been developed for prediction of the number of rainy days one month ahead of time with a spatial resolution of 10 × 10. The model accuracy is found to be 67.48