It is almost impossible to develop a wear-free electrode where the practical approach is followed to enhance the electrode life by modulating the process conditions for proper electrode material with geometric design of tip. The degradation of electrode for coated steel mainly occurs due to alloying of pure copper electrode that localize the heat generation randomly and impact on the nugget formation. Hence machine learning (ML) models are developed using cluster-based and feature-based algorithm to outperform the life of three different types of electrodes. Twelve independent features are considered and out of which the nugget diameter is the most sensitive feature on the electrode life. It means the evolution and formation of nugget at optimum weld lobe (range of current and electrode force) decides the number of welds the electrode can perform successfully since the electrode surface condition, specifically for coated steel, is having a direct impact on weld nugget formation. The present analysis shows that almost all ML algorithms performs well for choosing the best feature that impact on resistance spot welding of GA coated high strength bake hardened steel of 0.65 mm thickness.