The article presents a solution to balance user workload in cloud computing more efficiently. By predicting future user requests and mapping them to virtual machines based on their capacity, the model maximizes the serving number of requests. This approach uses big data and machine learning techniques to make accurate predictions. The evaluation of the model shows that it effectively distributes user workload and improves performance metrics compared to other methods.