Abstract: A method of estimating employee turnover rates obtains original employee data from a preset data source. First data processing is applied to the original employee data to obtain first processed employee data. A training set and a first verification set are selected from the first processed employee data. The training set is used to train a machine learning model to obtain a turnover estimation model. The first verification set is used to verify the turnover estimation model to obtain a first estimation result. The turnover estimation model is optimized according to the first estimation result to obtain an optimized turnover estimation model. Updated employee data and a corresponding employee turnover rate of a second time period are obtained. The method helps to replenish manpower in time and avoids over-recruitment.