Indian rainfall is influenced by various climate drivers and climate forcings, and its frequency and occurrence is also affected by global warming. The changes in Indian rainfall affect the agriculture and livelihood of billions of people and hence the economy of India. Therefore accurate prediction of Indian rainfall is necessary which requires a clear understanding of various climate drivers and climate forcings responsible for the Indian rainfall and the physical mechanisms underlying it. In addition to the commonly used proxies like ENSO, IOD, AMO, etc., new parameters based on the sea surface temperature over the Arabian Sea and Bay of Bengal and atmospheric moisture are introduced and analysed their influence on the Indian rainfall. The analysis is carried out using a multiple linear regression (MLR) model. This model helps to assess contributions of different remote and local climate drivers to seasonal and regional inhomogeneity in rainfall. It is found that the Indian Summer Monsoon Rainfall (ISMR) variability is governed by Eastern and Central Pacific El Niño Southern Oscillation, equatorial zonal winds, Atlantic zonal mode and surface temperatures of the Arabian Sea and Bay of Bengal. The North East Monsoon Rainfall variability is controlled by sea surface temperature of the North Atlantic and extratropical oceans. The ISMR shows statistically significant positive trends (0.43 mm/day/dec) in North West India. The influence of warming over the Indian Ocean on the Indian rainfall is studied using parameters created from the atmospheric moisture content, its transport and its divergence over the Arabian Sea, Bay of Bengal, central Indian Ocean and Ganga river basin using the MLR model. The study reveals that the ISMR is largely controlled by the Arabian Sea moisture flux and Ganga river basin moisture content, and these parameters exhibit statistically significant high correlations in most regions. The model reproduces rainfall variability of about 12–50%. Also, moisture indices could clearly identify the majority of wet and dry years.