Understanding the potential distribution patterns and responses to climate change of invasive plant species on a regional scale is of great significance for the prevention and control of invasive species. In the present study, the invasive plant species Xanthium spinosum L. (Bathurst burr) was studied in the Xinjiang region, where the species is widely distributed. Xinjiang was selected as the study region for constructing a BCC-CSM1-1 model developed by the China National Climate Center to simulate future climate conditions. A MaxEnt model and the ArcGIS spatial analyst tool were used to construct predictive models of suitable habitats for X. spinosum in the 2050s and 2070s under two future climate change scenarios (RCP 4.5 and 8.5). The ultimate aim was to quantitatively demonstrate the dispersal trends of X. spinosum in Xinjiang, variations in the area of suitable habitat, and the movement path of the center of distribution. The results indicated that annual precipitation, subsoil organic carbon content, topsoil pH, annual temperature range, seasonal variations in annual precipitation, and annual average temperature are dominant environmental factors that affect the geographical distribution of X. spinosum. Bortala, Tacheng, Northwest Altay, Central Hami, Northern Bayingol, Central Kizilsu, Northern Aksu, Kuytun City, Karamay City, Wujiaqu City, and Kashgar City were identified as areas with high invasion risk. Trends of a continuous increase in the area of suitable habitat at the respective levels and in the total area of suitable habitat for X. spinosum were predicted for both climate scenarios, with the responses being more sensitive in the RCP 8.5 scenario (high emissions). In general, the distribution of X. spinosum in Xinjiang has not reached saturation, with the species being radially dispersed towards the north piedmont of Tianshan Mountains and the northern margin of the Taklamakan Desert from the center of distribution in central Tacheng. The center of distribution is predicted to move towards Kuitun in Ili Prefecture by 2070 under both climate change scenarios.