This research aims to apply the K-Means Method and RapidMiner in identifying superior students based on the scores of Mathematics, Science, and Social Studies subjects at SMP Negeri 11 Sampit. With a dataset consisting of 24 attributes and 31 student data, the K-Means Method successfully clusters students based on the similarity of the grades the students obtained. The model evaluation results show that the best cluster value is 2 clusters. The use of the K-Means Method in this study is a solution to the difficulty in determining superior students at SMP Negeri 11 Sampit because students' abilities tend to be balanced in each semester. This research provides insight that the K-Means Method is effective in determining superior students and can be a useful tool in educational evaluation.