Background <p>Endometrial cancer (EC) is the most common cancer of the female reproductive system. Palmitoylation dysregulation is linked to various diseases. However, there is still insufficient research on its use as a prognostic marker for EC.</p> Methods <p>This research utilized transcriptomic data and clinical characteristics from EC patients sourced from the TCGA database. Key palmitoylation-related genes (PRGs) were identified through a series of bioinformatics analyses, followed by the construction of a prognostic model. The mRNA expression levels of characteristic genes in EC cells and clinical samples were investigated through reverse transcription quantitative polymerase chain reaction (RT-qPCR). Immune infiltration analysis was performed using ssGSEA and CIBERSORT. The molecular subtypes of EC were identified by consensus clustering.</p> Results <p>This study identified six PRGs, and the results of bioinformatic analysis of their mRNA expression patterns were consistent with experimental validation. A risk stratification model constructed based on these six PRGs was able to significantly distinguish between high-risk and low-risk patients in terms of survival prognosis, with patients in the low-risk group having a better prognosis than those in the high-risk group. Furthermore, immune characteristic heterogeneity was observed among different risk subgroups. Through consensus clustering analysis, EC samples were classified into two molecular subtypes with significant differences.</p> Conclusion <p>This study constructed and validated a prognostic risk model for EC based on PRGs, which demonstrated potential for stratifying patient survival rates and characterizing immune microenvironment features in a retrospective dataset.</p>