Machine Learning for Ensuring Sustainable Development: Predicting Employee Attrition in the Workplace

The present research provides a machine learning technique that uses Logistic Regression to predict employee turnover rates while accounting for critical parameters. The purpose is to prevent employees from leaving because it has a negative impact on organizational productivity, costs, and employee well-being. By analyzing data on employee demographics, work satisfaction, and other relevant variables, logistic regression is used to identify factors that impact attrition. In addition, the research investigates the effects of projecting employee attrition on long-term development goals like decent employment and economic growth, gender equality, excellent health and wellbeing, and reduced inequities. Organizations can promote long-term economic success while contributing to a more sustainable future by fostering a safe and productive workplace.