Abstract: On March 15, 2024, an extensive forest fire occurred in Yajiang County, Sichuan Province. In the first post-fire rainy season, hundreds of post fire debris flows(PFDFs) were triggered, providing a valuable dataset for studying PFDFs in southwestern mountainous regions. This study developed PFDF susceptibility and volume prediction models based on field investigations, UAV imagery, satellite remote sensing, and rainfall data. The models were constructed using the PFDF event database from the burned area of Yajiang County on March 15, 2024, and were subsequently applied to hazard prediction for two burned areas: Chengxiang Village (December 9, 2024) and Muzexi Village (February 2, 2025). The results show that: (1) The optimal Random Forest susceptibility model achieved an AUC of 0.905 and an accuracy of 0.950. For the Chengxiang and Muzexi burned areas, 10 and 22 catchments, respectively, were classified as extremely high or high susceptibility, accounting for 48.57% and 73.68% of their total watersheds. (2) The optimal factor combination for the volume prediction model included hourly rainfall intensity, percentage of catchment area with slopes exceeding 30°, soil clay content, gully density, normalized difference vegetation index (NDVI), and the moderate and severe burned area. The generalized additive model for volume prediction achieved an R²of 0.65. Under Q25%, Q75%, and P20% rainfall scenarios, the proportion of catchments in Chengxiang with debris flow volumes exceeding 200 m³ was 2.86%, 25.72%, and 34.29%, respectively, while in Muzexi, the proportion of catchments with volumes exceeding 1000 m³ was 0%, 15.79%, and 63.16%, respectively. Debris flow volumes in Chengxiang are generally smaller, but the area contains a high density of vulnerable elements, with catchments CX05, CX08, CX13, and CX25 posing significant hazards. In contrast, debris flows in Muzexi tend to have larger volumes, with catchments MZX02 and MZX04 identified as high-risk areas. This study provides a scientific basis for rapid assessment and targeted mitigation of PFDFs in Yajiang county.