Resumes or Curriculum Vitae (CVs) are still an important standard document and a decision element in evaluating the life journeys and human personalities of candidates. Its main role is to detect the eli-gibility of people who are applying to job vacancies or higher education programs. This research work ambitions in elaborating a system that au-tomates the preselection of eligibility and assessment of candidates in the higher education students’ recruitment process. This system will replace the tedious tasks of manual processing of CVs and will provide accurate and effective evaluation results. To achieve this requirement, the system will be implemented using a machine learning approach using different classification algorithms. The evaluation is conducted on the four main knowledge categories that build the CV: personal information, academic background, professional experience, and soft and technical skills. The output of the system will be an indicator to shortlist, discard or request more information to evaluate the candidates’ eligibility. Moreover, the scores obtained for each part of the CV will be used to calibrate the indicator in each information category. Consequently, this system boosts the recruitment process of candidates and provide a reasonable decision