Abstract: Industrial carbon emission reduction is a crucial strategy for China to achieve carbon neutrality by 2060. Based on energy data of Guizhou Province from 2010 to 2021, this study adopted the Logarithmic Mean Divisia Index (LMDI) method to identify the influencing factors of industrial carbon emissions during this period. Meanwhile, the STIRPAT model combined with ridge regression analysis was applied to predict industrial carbon emissions in the province from 2026 to 2035. The results showed that raw coal and electricity were the primary energy sources driving the increase of industrial carbon emissions in Guizhou Province. The decomposition analysis identified economic development as the dominant factor driving the increase of carbon emissions, with a cumulative effect value of 16.41 million tons and a total contribution rate of −1 185%, followed by the population size effect, with a cumulative effect value of 1.26 million tons and a total contribution rate of −91%. The energy consumption intensity contributed a cumulative effect value of −16.76 million tons, with a total contribution rate of 1 210%, while the energy structure effect showed a cumulative effect value of −2.29 million tons with a total contribution rate of 165%. Both factors exerted inhibitory effects on carbon emissions, and the inhibition from energy consumption intensity was stronger. The growth of per capita GDP is anticipated to drive up carbon emissions, with varying rates of increase across different regions or sectors. Industrial carbon emissions in Guizhou Province are expected to peak in 2030. Under a per capita GDP growth rate of 8% to 10%, the projected peak emissions range from 12.28 million tons to 12.51 million tons. After 2030, emissions are expected to decrease, with a 37.5% drop in 2035 relative to the peak. Among them, at a growth rate of 8%, emissions would drop from 12.28 million tons to 7.67 million tons and at a growth rate of 10%, they would decrease from 12.51 million tons to 7.82 million tons, reflecting significant decarbonization potential.