<p>Melanoma is a malignant tumor originating from melanocytes. Mitophagy, a specialized form of autophagy targeting mitochondria, plays a crucial role in selectively clearing damaged and aging mitochondria, exerting a double-edged sword effect in cancer cells. However, its impact on melanoma remains unclear. In this study, we utilized mitophagy-related prognostic genes (MPGs) and applied machine learning to construct a riskscore, stratifying melanoma patients into low-risk and high-risk groups. We then conducted immune infiltration analysis, differential expression analysis, and functional enrichment analysis. Our findings revealed that immune infiltration, including CD8⁺ T cells, NK cells, macrophages, and neutrophils, was higher in the low-risk group than in the high-risk group. Moreover, differential expression analysis indicated the activation of immune-related pathways, particularly the IFN signaling pathway, in the low-risk group. We further identified potential mitophagy-related hub genes and their cellular localization using quantitative PCR (qPCR) and single-cell analysis. Additionally, the pRRophetic algorithm was employed to predict potential therapeutic benefits for patients with different riskscores. In conclusion, MPGs expression appears to be correlated with increased immune activation and IFN signaling in the tumor microenvironment, which may be linked to better outcomes in melanoma patients.</p>