This project aims to predict attrition of employee based on data sourced from HR department. This data includes columns for Age, Attrition, Department, Gender, Salary, Education Level, Role, Hours Worked among others. The target variable here is the Attrition column with values Yes or No. The other 34 variables are used in predicting the target using a classification machine learning model. Performance of the model will also be evaluated using the McFadden R2 and confusion matrix. Lastly, factor importance will also be determined to ascertain the most important features driving staff to leave or stay with the company. This will enable HR can formulate appropriate staff retention strategies.