This paper is presented with the implementation of Leader-Follower clustering algorithm to improve the efficiency of clustering in k-means clustering algorithm. This Leader-follower algorithm, though unstable, can be implemented with clustering algorithms, leading to the improved efficiency of the clustering. Clustering is the process of grouping a given data set upon the characteristics they possess. K-means clustering algorithm has its main concentration on the centroids, which leads to clustering of the data. Leader-follower is a clustering algorithm that clusters data upon a given threshold. Here, the output of Leader-follower is taken and is fed as input to k-means, which refines the clustering process with improved centroid selections, that leads to effective clustering.