【Aim】 Sphaerolecanium prunastri, a scale insect which harms wild fruit forests in western Tianshan, Xinjiang, is inducing massive mortality of Prunus armeniaca and the decline of ecosystem health and services. The potential suitable habitats in China under future climate scenarios were predicted, which can provide scientific basis for the prevention and control of S. prunastri in agriculture and forestry departments. 【Method】 Based on the collection of geographical distribution points of S. prunastri and global meteorological data, MaxEnt model was used to predict and analyze the potential suitable habitats in China. 【Result】 The average AUC of the MaxEnt model was 0.949, suggesting the prediction results highly reliable. The main environmental variables affecting the potential distribution of S. prunastris were min temperature of coldest month, precipitation of coldest quarter, standard deviation of temperature seasonal change and isothermality. The results showed that S. prunastri could have a wide potential distribution in China. The model predicted that S. prunastris's highly suitable habitats were mainly distributed in Bohai Coastal Region of Liaoning Province, Hebei Province, Beijing, Tianjin, Shandong Province, Henan Province, central Shaanxi Province, as well as the border area between Gansu Province and Shaanxi Province, and the Yili Kazakh Autonomous Prefecture, Bayingol Mongolian Autonomous Prefecture, and Altay region of Xinjiang Uygur Autonomous Region.The moderately suitable habitat were mainly distributed in Liaoning, Inner Mongolia, Shanxi, and Xinjiang. The area ratios of highly suitable habitats, moderately suitable habitats, and low suitable habitats were 4.62%, 6.69%, and 18.77%, respectively. Under the future climate scenario, the highly suitable habits showed a dispersion trend, especially in Xinjiang. 【Conclusion】 The habitats suitable for S. prunastri account for 30.08% of all land area, with a risk of continued spreading and invading outbreaks, especially in the northwest and north of China. Relevant departments should pay attention to it.