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Inflammatory infiltration plays an essential role in the progression of tumor malignancy. The aim of this study was to identify genes associated with inflammatory microenvironment and clinical traits for survival prediction of uveal melanoma (UVM) patients. The datasets and clinical characteristics of UVM were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We divided the UVM patients into low and high immune cell infiltration groups, identified differentially expressed genes (DEGs), constructed weighted gene co-expression network, and established prognostic prediction model and nomogram for UVM. Our analysis showed that DEGs were enriched in cytokine signaling in immune system, positive regulation of immune response and adaptive immune system. A total of fifteen candidate genes were extracted from DEGs and genes that were positively associated with tumor metastasis. Subsequently, five prognostic genes were selected to construct the final prognostic prediction model, including two up-regulated genes LHFPL3 antisense RNA 1 (LHFPL3-AS1) and LYN proto-oncogene (LYN), and three down-regulated genes SLCO4A1 antisense RNA 1 (SLCO4A1-AS1), Zinc-α2-glycoprotein 1 (AZGP1) and Deleted in Liver Cancer-1 (DLC1) in the high risk group. The model showed an Area Under Curve (AUC) value of 0.877. Our analysis highlighted the importance of immune-related genes in the progression of UVM and also provided potential targets for the immunotherapy of UVM.