Abstract: Based on the overall carbon emissions and related data of Guangdong Province from 1998 to 2019, six indicators were selected as influencing factors of carbon emissions, namely permanent resident, per capita GDP, proportion of the secondary industry, energy structure, energy intensity, and carbon intensity. By integrating the extended STIRPAT model with ridge regression, a fitting regression equation for predicting carbon emissions was constructed using the data of these indicators from 1998 to 2019. Additionally, scenario analysis was employed to divide the period from 2020 to 2035 into three phases, and three scenarios were set to forecast the peak of carbon emissions. The results indicate that under the unregulated scenario, the carbon emissions in Guangdong Province will continue to rise without reaching a peak. In the regulated scenario, carbon emissions will peak at 7.022×10⁸ tons in 2030, while in the strongly regulated scenario, the peak will occur in 2025, with a value of 6.430×10⁸ tons. The research provides a theoretical referance for the green and low-carbon transformation development of Guangdong Province.