In the development procssess of the copper industry, traditional intelligent decision-making systems have problems such as data silos, limited analytical capabilities, and difficulty in responding to rapid market changes, which limit the efficient and sustainable development of the copper industry. To address these issues, this article applies cloud computing to the construction of an intelligent decision-making system. By integrating multiple sources of data such as copper production, market, and supply chain, the elastic computing resources and big data processing capabilities of cloud computing are utilized to achieve centralized management and real-time analysis of data. Moreover, this article adopts the random forest algorithm to model and predict the grade of copper concentrate in the copper flotation process. By constructing a prediction model and optimizing algorithms, intelligent decision support such as market trend prediction, production optimization suggestions, and risk assessment is provided. In addition, the system can monitor production and market dynamics in real time, achieving dynamic adjustments and rapid response. The research results indicate that using cloud computing to build an intelligent decision-making system for the development of the copper industry has significant advantages in data integration, analysis, and response speed. The overall response speed score is 97.45 points, especially in real-time monitoring ability, reaching 99.5 points, highlighting the powerful capabilities of cloud computing technology in processing speed and efficiency.