Human Resources or Human Capital is the core component for the progress and success of any organization. The employees within an organization constitute its most valuable asset, as they are the driving force behind innovation, the delivery of products & services, and customer interactions. Organizations are investing in capacity building and upskilling their resources. Therefore, it is essential to retain the resources for the development and growth of any organization. The task of managing these kinds of situations is a major challenge for any human resource department. The proposed work aims to offer a solution to this significant issue. The paper presents a possible solution based on a case study of an ITES company. Machine learning, the popular technique is used to predict the possibility of attrition and is useful to get its possibility. It is very difficult to trust the feedback of the person willing to leave the company. Therefore the clustering is used through the k-means technique to handle the output of this problem. The results of the solution are very effective and efficient in giving the solution to the problem of attrition.