Nowadays, the corporate world not only prioritizes an individual's skills but also their personality traits, as they play a crucial role in achieving success both professionally and personally. Therefore, recruiters must have knowledge of potential employees' personality traits. However, due to the significant increase in job seekers and the decline in job availability, it is challenging to manually select the most suitable candidate by just reviewing their resume. This analysis aims to explore various machine learning techniques for predicting personality traits effectively by analyzing resumes through Natural Language Processing (NLP) methods. The research demonstrates that the Random Forest algorithm outperforms other approaches such as k-Nearest Neighbors (kNN), Logistic Regression, SVM, and Naive Bayes in terms of accuracy.