It is important to assess the impact of climate change on ecosystems for ecological conservation. Climate–vegetation models are considered to provide an effective way of demonstrating climate change impacts. One such model, Köppen Classification, is widely used to estimate the effects of global climate change on ecosystems. However, due to climate surface resolution limitations, previous studies have not been able to completely reflect the impact of climate change on different ecosystem types in some mountain areas. Sichuan Province, which is located in the southwest of China, is sensitive to climate change because of its complex topography. In this paper, we used Köppen Classification to quantify the changes of bioclimatic types for Sichuan Province under climate change. We employed Regional Climate Model 4.0 to project monthly temperature and precipitation from 1981 to 2099. Then, the model output was calibrated by using data from 204 meteorological stations in and around Sichuan Province. Subsequently, spatial interpolation software, Anusplin 4.3.6, was used to downscale temperature and precipitation data, using elevation as an independent covariable. A 1 km x 1 km spatial resolution was selected for the climate data. Considering the uncertainty in climate change, we selected three time periods to analyze the distribution of Köppen climates, including 2010 (representing the 30-year average for 1981-2010), 2040 (representing the 30-year average for 2011-2040), 2060 (representing the 30-year average for 2031-2060), and 2099 (representing the 30-year average for 2070-2099). The 1981-2010 period was used as a baseline to represent "current climate." First, we found that there were three bioclimatic types in the current period, including temperate climates (C), continental climates (D), and polar climates (E). C type, D type, and E type climates cover 54%, 22%, and 24% of the total area in Sichuan Province, respectively. Second, we found that the spatial patterns of bioclimatic types will not noticeably alter between 1981 and 2099, because neither new types nor current types appear or disappear, respectively. However, the changes in temperature were sufficient to cause shifts in bioclimatic types. Between 1981-2010 and 2070-2099, the areas covered by C and D types will increase by about 13% and 20%, respectively. In contrast, the relative area covered by E type during this period will decrease by about 48%. The maximum shift mainly refers to E type, while the maximum shift was observed for both E to D types. In addition, our results indicate that bioclimatic types display different rates of shifts in different time periods. For instance, the rate of change in 2011-2040 is greater than that in 2031-2060 and 2070-2099. Therefore, the response of ecosystem types to climate change in Sichuan Province is expected to be more drastic in the near future (2011-2040) compared to the distant-future (2031-2060 and 2070-2099). Third, we found that all the distribution of all types would shift in space, moving towards higher altitudes. Between 1981-2010 and 2070-2099, the shift rates along altitudinal gradients for C, D, and E types is expected to average 2.9 m per year, 3.4 m per year, and 1.8 m per year, respectively. By calculating the changed area in elevation zones of 100 m intervals, the changed area will be concentrated at an elevation range of 3800 m to 4500 m. Therefore, elevation zones should be considered for ecosystem conservation under climate change.