In recent years, sustainable development has become a key factor in the invention and use of new technologies. The automotive sector is known for its high energy consumption, most of which is from conventional fuels. Due to environmental restrictions, the use of natural gas to power automotive engines has received significant attention, and this has driven the development of new technologies. This includes Homogeneous Charge Compression Ignition (HCCI), which enables hybrid operation in cars. Switching from petrol or diesel to biogas, mainly methane, has also become feasible due to advances in biomass research. The utilisation of compressed natural gas (CNG) in the direct injection SI engine or as a dual fuel in the CI engine is projected to replace conventional fuels in the years ahead. Artificial intelligence has received dramatic attention recently in different energy sectors. In this chapter, the prediction of combustion characteristics of a supercharged direct injection compressed natural gas (CNG) engine was carried out using Artificial Neural Networks. It was observed that the ANN predicted combustion characteristics with an R2 of 0.99 and very low mean squared error, indicating that the ANN is the most effective tool for predicting these characteristics and minimising the performance gap between alternative and conventional fuels for the greener automotive sector ahead.