Abstract: The Jiurui region in Jiangxi Province, China, is one of the most significant copper mining areas in the middle and lower reaches of the Yangtze River mineralization belt, with a close relationship between granodiorite porphyry and copper mineralization. In this study, a predictive model for mineralization potential was established by combining factor analysis (FA), concentration-area (C-A) fractal method, and fuzzy weight of evidence (FWofE) based on information related to stream sediment and mineralization. ϕfactor analysis was applied to a dataset of 255 stream sediment samples containing 32 elements to identify combinations of elements (principal factors) indicative of copper mineralization. κ the principal factor scores were interpolated using the multiple inverse distance weighted (MIDW) method to create a raster map, and the C-A fractal model was employed to extract geochemical anomalies associated with copper mineralization. λ the geochemical anomaly map related to copper mineralization was integrated with geological and remote sensing interpretation data, and a predictive model was established using the fuzzy weight of evidence method. The results indicated that: known copper deposits are located within high-probability zones defined by the model and are influenced by the distribution of granodiorite porphyry and faults; in addition to the known copper deposit areas, three primary prospective areas identified within the defined regions also exhibit a high probability, meriting further exploration efforts for copper prospecting.