Background:　Skin　melanoma　exhibits　significant　heterogeneity　in　clinical　outcomes　and　treatment　responses　among　patients.　This　study　aimed　to　investigate　natural　killer　(NK)　cell　clusters　in　skin　melanoma,　their　impact　on　patient　prognosis,　and　their　value　as　biomarkers　for　tailoring　treatment.　Methods:　We　used　data　from　TCGA,　GSE19234,　GSE65904,　GSE244982,　and　GSE78220.　A　gene　classifier　was　developed　to　identify　two　distinct　clusters　of　melanoma　patients.　Survival　analysis,　NK　cell　infiltration　levels,　and　responses　to　immune　and　targeted　therapies　were　evaluated.　Results:　Unsupervised　clustering　revealed　two　distinct　melanoma　patient　clusters　with　significant　differences　in　NK　cell　activity　and　clinical　outcomes.　Cluster　1　showed　higher　NK　cell　infiltration,　better　overall　survival　(OS)　(p　＜　0.0001),　and　greater　activity　in　NK-cell-related　pathways.　In　contrast,　Cluster　2,　characterized　by　lower　NK　cell　activity　and　higher　exhaustion　markers,　had　poorer　OS.　Drug　sensitivity　analysis　indicated　that　Cluster　1　was　more　responsive　to　most　melanoma　treatments,　whereas　Cluster　2　had　higher　sensitivity　to　trametinib　(p　＜　0.001).　The　developed　gene　classifier　had　an　AUC　of　0.913　and　effectively　differentiated　between　clusters.　Additionally,　Cluster　1　showed　better　responses　to　immunotherapy　with　a　higher　rate　of　complete　and　partial　responses　(p　＜　0.001).　These　findings　were　validated　in　external　databases.　Conclusion:　This　study　identifies　two　distinct　NK-cell-related　clusters　in　melanoma　with　differential　prognoses　and　treatment　responses.　These　findings　underscore　the　importance　of　integrating　NK-cell-related　profiles　into　personalized　treatment　strategies,　offering　a　pathway　to　optimize　therapeutic　outcomes　based　on　specific　immune　profiles.　©　2025　The　Author(s).　Immunity,　Inflammation　and　Disease　published　by　John　Wiley　&　Sons　Ltd.