Abstract: Industry is the main field of carbon emissions from energy consumption, this paper takes China's industrial sector as the main research object, decomposes the factors affecting China's industrial energy consumption carbon emissions into four aspects such as economic growth, energy intensity, energy structure, and industrial structure by using LMDI method, and constructs an extended Ridge regression method based on measuring China's industrial sector carbon emissions from 2005-2019 STIRPAT model, combined with the scenario analysis method, to predict the carbon peak year and peak value of China's industrial sector. The results show that economic growth is the most important factor affecting carbon emissions, and energy intensity has a strong negative impact on carbon emissions. Under the baseline scenario, the industrial sector peaks in 2035. In order to achieve the goal of peaking by 2030, this paper optimizes the pathway in terms of changing the economic growth mode, optimizing the industrial structure, and improving energy efficiency, so that the peak year of China's industrial sector is advanced to 2028.