The Micro, Small, and Medium Enterprises (MSME) industry in India, where effective resolution of conflicts can significantly impact organizational performance, workplace fairness, and overall business outcomes. Our proposition through this research is a novel machine learning approach to conflict management with association of ego states of the employees by studying the transactions. Specifically, we target 200 working professionals in the field of operations management, aiming to assess their conflict management styles. Our research leverages machine learning techniques to analyze and interpret the choice of conflict management style among MSME professionals and explore their implications for workplace well-being. By integrating the data based on ego states of employees with machine learning algorithms, we studied the relationship between ego states and conflict management styles of the employee in the current organization. This transaction analysis while choosing an individual style of conflict (by employees) leads to surprising results. Through surveys, interviews, and data analysis, we aim to elucidate how ego states influence conflict management styles, decision-making processes, and interpersonal dynamics within MSME organizations. By understanding the relationship between ego state of employee and conflict management strategies, wend favor to develop insights and recommendations to enhance conflict resolution effectiveness and promote a harmonious work environment within the MSME sector.