Geochemical anomaly mapping is a significant aim in exploring for Au and associated elements using fine fraction sediments. The fractal behavior of geochemical elements has frequently been modeled for geochemical prospectivity mapping. In this study, concentration–area (C-A) and power spectrum–area (S-A) fractal modeling were utilized for Au concentration in stream sediments near the Saqqez mineralization area, NW Iran. Therefore, a novel integrated approach based on the S-A fractal method and principal component analysis (PCA) was used to improve the geochemical anomaly map. In this approach, the multi–element mineralization factor returned from PCA was modeled by the S-A fractal method, and the obtained results were compared to the C-A and S-A fractal models of the Au element. Six known mineralization zones in the studied area were revisited for validating the fractal models. The elements Au, As, W, and Sb were identified as associated elements based on the log-ratio transformed data in the shear zone gold mineralization. The spectrum – area fractal modeling of multi-element mineralization factor (SAF-MF) of the Au-associated elements in the mineralization zones enhanced the geochemical halos and increased the prediction rate of mineralization zones using the stream sediment geochemical data. The SAF-MF that models the behavior of frequency signals of associated elements upgraded the geochemical anomaly mapping compared to the conventional fractal models.