The Indian electricity sector has come a long way since the country’s independence by ensuring electricity availability to its remotest corners. However, the sector is still plagued with twin issues of high dependence on fossil fuels and excessive electricity transmission and distribution (T&D) losses. The high losses are determinants of the electricity sector’s financial health and need to be viewed from an environmental perspective if India’s high dependence on fossil fuels for electricity generation is considered. The historical information related to the T&D losses reveals that policy instruments aimed at plugging the leakages had a minimal effect on them. This historical information can also help construct an expected long-term future scenario. Accordingly, the study, by utilizing the historical information (1980-2018) for T&D losses in the Indian electricity sector, endeavors to predict its future scenario (2019-2035). The study compares the suitability of grey forecasting methods such as Metabolic grey model, Non-linear Metabolic grey model with popular machine learning methods such as Support Vector Machine, Multilayer Perception and Extreme Gradient Boosting to provide accurate long-term predictions in the present context. The results indicate that in the absence of any new major policy initiatives, the T&D losses will be approximately 15-20% of India’s aggregate electricity consumption by 2035, which is still very high considering the expected growth in India in the same period. Thus, the study results indicate the requirement of an exhaustive policy at the country’s level, which is backed at the implementation level by various state governments.