The complex, nonlinear relationship among the components of high-performance concrete (HPC) poses a significant challenge in modeling its compressive strength. Prior studies have consistently found it challenging to maintain a balance among various factors, including mix proportions, material properties, curing conditions, ambient conditions, and concrete age. Nevertheless, in concrete mix design and quality control, compressive strength remains the primary indicator of HPC quality. This study proposed an ensemble model constructed using a metaheuristic optimization algorithm to predict the compressive strength of HPC. Three datasets are utilized to assess the performance of both single and ensemble models. The optimal results will be further compared with those from prior studies. Analytical results indicate that the proposed ensemble model outperforms others in predicting the compressive strength of HPC.