Machine Learning Based Employee Attrition Prediction and Layoff Prediction System

B. Suchithra; M. Pushpalatha; N. Ramesh; G. Sumithra; S. Siva Sankar

Machine Learning Based Employee Attrition Prediction and Layoff Prediction System

Author(s)	B. Suchithra, M. Pushpalatha, N. Ramesh, G. Sumithra, S. Siva Sankar
Country	India
Abstract	Now a days Employee attrition is a major issue faced by many organizations, as it leads to increased costs and loss of experienced employees. When employees leave a company frequently, it affects productivity and overall organizational growth. Therefore, predicting employee attrition in advance is important for companies to take preventive actions and improve employee retention.his project focuses on predicting employee attrition using machine learning techniques. Employee data such as age, job role, salary, experience, job satisfaction, and working conditions are analyzed to understand the factors influencing attrition. Before building the model, data preprocessing techniques are applied to clean and prepare the dataset. Machine learning algorithms such as Logistic Regression, Decision Tree, and Random Forest are used to build an effective attrition prediction system.The proposed machine learning-based employee attrition prediction system helps organizations identify employees who are at risk of leaving the company. By predicting attrition in advance, HR departments can take timely actions such as improving work conditions, offering incentives, and providing career growth opportunities. This system supports data-driven decision making and helps organizations improve employee retention and long-term performance.
Keywords	Employee Attrition, Layoff Prediction, Machine Learning, HR Analytics, Classification Models, Predictive Analysis,Random Forest Algorithm.
Field	Engineering
Published In	Volume 7, Issue 4, April 2026
Published On	2026-04-04

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Machine Learning Based Employee Attrition Prediction and Layoff Prediction System

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