Making decision can have a vital role in the administration and might indicate the most significant constituent in the route of planning. Attrition of employees is a well-known issue that requires the correct judgments from the management to keep highly skilled employees. Excitingly, Artificial Intelligence (AI), Machine and Deep Learning were applied broadly for instance like an effective means for the prediction of employee attrition. The aim of this study was to utilize machine and deep learning models to predict employee attrition with a high accuracy; furthermore, to identify the most influential factors affecting employee attrition. The dataset used in this study was collected from Kaggle Depository. The dataset was created by the IBM analytics that consists of 35 features from 1,470 employees. To get the best accuracy of prediction of employee attrition, we preprocessed the dataset, balanced it and split it into three sets: train, valid, and test datasets. Several experiments were carried out to show the practical value of this study. The deep learning model archived f1-score of (94.52%), recall (94.52%), and precision (94.58), accuracy (94.52%), whereas the best machine learning model archived f1-score (92.52%), recall (92.55%), precision (92.52), and accuracy (92.55%) for the prediction of employee attrition.