This study focuses on the integration of geochemical data analysis methods to enhance mineral exploration in the Siah Cheshmeh region of the Khoy Ophiolite in northwestern Iran. Initially, all preprocessing steps were applied to the geochemical data to ensure its quality and accuracy before proceeding with the main analysis. Staged Factor Analysis (SFA) was then employed to identify key elements closely related to mineralization processes, such as Au, Cu, Fe, Mn, Zn, Cr, and Ni, due to their significant roles in mineral enrichment and deposit formation. These elements were subsequently analyzed using Exploratory Data Analysis (EDA) and fractal modeling techniques to differentiate background from anomaly concentrations, effectively detecting high-anomaly areas indicative of mineral-rich zones. For example, the anomaly area for manganese using the fractal method was determined to be 4,551,879 square meters, compared to 22,107,400 square meters obtained using EDA, highlighting the fractal method's higher precision in mapping anomalies. The SFA approach was further refined using the Geochemical Mineralization Potential Index (GMPI), with calculations performed for the associations GMPIAu-Cu-Fe-Mn-Zn and GMPICr-Ni. GMPI values were determined based on the 95% cumulative frequency, with additional thresholds at 99% and 97.5% to highlight higher-intensity anomalies. This comprehensive integration of SFA, EDA, fractal modeling, and GMPI methods produced detailed geochemical maps that precisely identify prospective exploration areas, emphasizing regions with high mineral potential. The study demonstrates the effectiveness of combining these techniques to guide focused geochemical investigations for mineral exploration.