Individuals play a significant role to enhance and accelerate the performance of the organizations and hiring right employees, is indeed a challenging task. It is because many people show interest in the single job opening. HR in large organizations, recruits and explores such people by following proper recruitment process. This recruitment process has been proven to be lengthy, tidy and costly because of a substantial number of applicants. Recruitment of suitable individuals becomes more difficult for smaller organizations as they do not have HR department. Automation can improve the process though. By doing this, the process becomes shorter, easier, and cost effective. In that respect several automated recruiting systems have been proposed in the literature. The primary limitation of the existing recruitment systems is that it simply picks out those candidates who meet the (100%) skills set and turns down the rest of them yet if they are meeting the partial criteria. It intends that as these programs have been projected to pick only those who are gathering all the prerequisites. In fact, the recruitment system can select the candidates that are even meeting the near about or close requirements. It is because if a candidate does not meet (100%), then the candidate with the lesser requirement should be kept under consideration. There can be chances where a person meeting 9 out of 10 requirements could have proved to be the best choice, but because of the system we lose such candidates. The current research proposes a Fuzzy logic-based decision support system (DSS), to overcome the above-mentioned limitation. Abiding by the Fuzzy logic, the proposed system can view the partial skills of the applicants. The system has been validated by implementing the prototype. The outcomes depict a significant improvement to overcome the limitation of the existing recruitment systems.