Effective resolution of conflicts can significantly impact organizational performance, workplace fairness, and overall business outcomes. In this study, we propose a novel machine learning approach to predict conflict management style (dependent variable) based on gender and work experience (both independent variables). For this, we gathered information from 200 working professionals in different sectors in India, such as logistics, manufacturing, and consultancy firms. We started with a chi-test to understand the association between dependent and independent variables. Once association was observed, we explored the machine learning models and finally narrowed it down to a random forest algorithm after examining classification accuracy. Our results indicate predictions for males and professionals at the junior level for their Conflict Management Style (CMS). Professionals employed competing, accommodating, and collaborating styles to address conflicts. Style prediction can help stakeholders make relevant decisions in conflicting situations.