Abstract: The exploration and development of coalbed methane are facing increasingly complex challenges, accompanied by a worsening of the quality of resources. It is imperative to address the technical challenges of identifying the primary control factors and mechanisms for high coalbed methane production, establishing a reliable integrated geological-engineering evaluation method, enhancing the accuracy of dynamic coalbed methane prediction, and improving the effectiveness of engineering decisions. Building upon research achievements related to regional data repositories and detailed descriptions of gas reservoirs, and leveraging artificial intelligence technology, a comprehensive data mining effort was conducted on coalbed methane reservoirs. This innovative approach led to the development of an integrated intelligent decision-making system for coalbed methane geological and engineering activities, based on big data analysis algorithms. This system integrates and manages data related to coalbed methane geological, gas reservoir, and engineering aspects, offers rapid predictions of single-well gas production under big data-driven conditions, analyzes the primary control factors, conducts comprehensive analyses of coalbed methane reservoir parameters by incorporating geological and engineering factors, and optimizes fracturing parameters based on post-fracturing production analysis. The system was piloted in the Daning-Ji xian block in the eastern margin of Hubei, and its subsequent widespread application significantly improved the efficiency of gas reservoir research and the effectiveness of engineering decisions. It provided strong support for gaining a comprehensive understanding of the resource potential of gas reservoirs and advancing the deep application of intelligent technology in research and production.