Grassland is a major vegetation type in Xinjiang Province, and is an important component of carbon source-sink calculations. It is therefore important to ecological management decisions to understand the factors driving changes in grassland quality and likely future trends in those changes. We used geographic information maps to eliminate the interference of human activities and determine changes in grassland status and areas of stable grassland from 1980 to 2020, and analyzed changes in grassland quality and its response to climate change using data such as normalized vegetation index (NDVI), vegetation net primary productivity (NPP), and meteorological data, among others. We here estimate changes in grassland quality in Xinjiang and predict grassland quality changes from 2021 to 2040 using the Thornthwaite Memorial model and other models. We found that: 1) The grassland quality in Xinjiang was generally increasing, with a statistically significant rate of ongoing increase. The grassland cover and quality in mountainous areas of Xinjiang was high, while that at the desert edge was low. 2) The main driving forces for grassland quality changes in Xinjiang are temperature and precipitation. The correlation between grassland quality and precipitation was positive. Temperatures exceeding a certain limit were found to inhibit grassland quality. Sensitivity to temperature and precipitation decline was found to be greater when vegetation cover was lower. 3) The grassland quality and its temporal and spatial changes in Xinjiang can be reflected by climatic productivity. The lower the grassland cover, the stronger was the link between grassland quality and climate factors. 4) Under currently predicted climate change scenarios, the quality of low-cover grassland will be improved in the future, while the quality of other categories will tend to decrease. This information on grassland quality in Xinjiang and its predicted future trends can assist in formulating ecological protection measures and in other ways, such as compilation of carbon stock inventories.