Abstract: In this paper, weexamined K-means clustering algorithm as one of the methods of data clustering and analysis process. The proposed study investigated the k-means algorithm with different size of samples. This study was tested the diabetes UCI standard dataset as case study. We start our experiments with 1015(Random number) sample size, and then we increase the sample size for each run by 1015 units. The elapsed time for each tested was calculated and reported for investigation process. Our investigation procedure was conducted using the R software..