Predicting the potentially geographical distribution of invasive species and rapidly assessing their high vulnerability areas are important means to realize the prospective risk warning of invasive species. At present, the MaxEnt niche model is the most widely used habitat risk assessment method with simple operation and high prediction accuracy, but it is too dependent on the quality and quantity of data. This study took Bemisia tabaci as the object, introduced geographic detectors to explicitly describe the spatial correlation and contribution of evaluation factors, and combined with the MaxEnt niche model to propose a mixed habitat risk assessment model (Geo-Maxent) and compare with the single MaxEnt niche model. The results showed that:(1) Geo-detector model showed that altitude (0.56), land use (0.43), the max temperature in the warmest month (0.36) and annual average temperature (0.30) had significant effects on the spatial distribution of Bemisia tabaci, and there were significant differences in the effects of various factors on the habitat of Bemisia tabaci. In addition, the PD(Factor detection) values of altitude and land use were high, indicating that altitude and land use are the main driving factors affecting the habitat of Bemisia tabaci. Besides, the interaction of environmental factors strengthened the influence of each single factor. (2) The overall accuracy of the single MaxEnt niche and the constructed model was 94.86% (AUC is 0.91) and 98.13% (AUC is 0.94), respectively, indicating that the accuracy of the constructed model was higher. (3) As for the high risk regions, the mixed model is better than the MaxEnt model, but the spatial distribution is highly consistent, mainly in the eastern region. As for the unsuitable regions, the results of the two models are consistent, and the unsuitable regions of the MaxEnt model are slightly larger than the mixed model. Geographic detectors can explain the interaction and synergistic effects of invasion driving factors, and can better express the ecological significance of habitat suitability and candidate factors of invasive insects, which is more effective in evaluating the habitat risk of invasive insects.