Aiming at the problems of low accuracy, slow speed, and poor robustness of the current algorithm in solving the clustering problem, an improved butterfly optimization clustering algorithm was proposed. Based on the idea of elite strategy, the local search iterative formula of butterfly optimization algorithm was redefined, and then the selection, crossover, and mutation operations of genetic algorithm were fused. Test results on one artificial dataset and five UCI datasets demonstrate that the performance of the proposed algorithm is superior to other algorithms.