## 6 Conclusions  
Mountainous areas significantly heighten the risk of rockfalls along highways due to their unique geological and topographical conditions. This increased risk poses a serious threat to traffic safety and infrastructure. Consequently, conducting a comprehensive assessment of rockfall risks in these terrains is essential to effectively mitigate hazards and enhance safety measures. In this research, the risk matrix combining highway rockfall susceptibility, highway rainfall hazard, and highway rockfall vulnerability was used to assess the highway rockfall risk in Guizhou Province and to characterize the distribution and influencing elements of rockfall risks in Guizhou Province. This research aims to provide valuable insights for local authorities and stakeholders, informing risk management strategies, enhancing safety protocols, and supporting infrastructure planning in areas prone to rockfalls. The main conclusions are as follows:  
1. The total highway rockfall risk in the whole of Guizhou Province is high. High-risk areas dominate, making up 41.19% of the total risk area. Medium-risk and low-risk areas account for 28.09% and 18.87%, respectively, while very high-risk areas represent just 11.84%.
2. The highway rockfall risk in Guizhou Province is characterized by a high spatial distribution in the west and a low spatial distribution in the east. BJ has the largest percentage of highway mileage that is above the high-risk level, over 70%, while QDN has the largest percentage of road mileage that is below the medium-risk level, over 75%.
3. A logistic regression analysis revealed that the RWI is the most important factor influencing highway rockfall susceptibility. The distance from the fault is the most negatively correlated indicator of highway rockfall susceptibility. The elevation has the least effect on the susceptibility to highway rockfalls.
4. By extracting the risk probabilities of disaster and non-disaster points and plotting the ROC curve, its AUC value reached 0.827. This proves that the model of this study is highly accurate.  
**Author Contributions:** Methodology, J.Y. and Z.X.; Validation, Z.X. and M.H.; Formal analysis, Z.X. and M.G.; Resources, M.G. and M.H.; Data curation, J.Y.; Writing--original draft, J.Y.; Writing--review & editing, M.H.; Visualization, M.G.; Supervision, S.Z.; Project administration, S.Z.; Funding acquisition, S.Z. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by Science and Technology Program of Guizhou Provincial Department of Transportation (2025-112-018; 2023-312-030); Science and Technology Infrastructure Program of Guizhou Province (2020-4Y047), Natural Science Foundation of China (Grant No. 12062026), Natural Resources Science and Technology Project of Fujian Province (KY-070000-04-2021-025), and the Postgraduate Scientific Research Innovation Project of Hunan Province (CX20240432).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Acknowledgments:** The authors would like to thank the Guizhou Provincial Government for providing the geological disaster data used in this study.  
**Conflicts of Interest:** Author [PERSON] was employed by the company Guizhou Traffic Construction Quality Supervision. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.