The biological constitution is fundamentally shaped by emotions, which accompany people to work every morning and shape doing so. Emotional intelligence (EI) is our primary emphasis, and we integrate it with data mining technology. The employment of different machine learning algorithms to control employees' emotions is one of the most fascinating research projects in the modern world. This study aims to identify the important emotional intelligence dimensions influencing the Keeping work and life in balance of employees in Chennai's IT companies. It also establishes a conceptual framework for machine learning and explainable artificial intelligence (ExAI)-based analysis using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modelling (SEM), and multiple regression analysis. With factor loadings above 0.85 and Composite Reliability values above 0.88, the validated measurement model demonstrated exceptional reliability and validity, and the suggested framework successfully identified five significant Emotional Intelligence dimensions that explained 72.37% of the total variance. Additionally, the SEM analysis verified that the most significant determinants of workers' Keeping work and life in balance were self-awareness (β = 0.684) and self-regulation (β = 0.612), offering a statistically supported basis for the suggested conceptual ML–ExAI framework.