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Esophageal cancer is a highly aggressive malignancy with a poor prognosis. More precise prognostic biomarkers are therefore needed. Disulfidptosis is a recently identified form of regulated cell death driven by disulfide stress. It has been implicated in tumor progression. However, its prognostic role in esophageal cancer remains largely unexplored. This study aimed to develop a disulfidptosis-related gene signature for risk stratification and outcome prediction in esophageal cancer patients. Based on 23 disulfidptosis-related genes, consensus clustering was performed to identify molecular subtypes. Differentially expressed genes (DEGs) between subtypes were subjected to functional enrichment, immune microenvironment, and drug sensitivity analyses. Univariate and multivariate Cox regression were used to construct a prognostic risk model, which was evaluated using time-dependent receiver operating characteristic (ROC) curve and Kaplan–Meier analysis. A clinical nomogram integrating the risk score and clinicopathological factors was developed and validated. Two distinct disulfidptosis-related subtypes were identified, showing significant differences in gene expression, immune infiltration, and stromal scores. A total of 1080 DEGs were enriched in pathways related to epidermal differentiation, NRF2 signaling, and glucocorticoid receptor activity. A five-gene prognostic signature was established and effectively stratified patients into high- and low-risk groups. The risk model exhibited strong discrimination for 1-, 3-, and 5-year overall survival outcomes. The predictive accuracy was further maximized through an integrated clinical nomogram, which achieved an outstanding area under the curve (AUC) of 0.94 for 5-year survival predictions. Drug sensitivity analysis revealed subtype-specific therapeutic vulnerabilities, supporting potential precision treatment strategies. This study proposes a novel disulfidptosis-related five-gene signature and nomogram that robustly predict prognosis in esophageal cancer. The findings highlight the clinical relevance of disulfidptosis in tumor biology and offer a potential tool for risk stratification and personalized therapeutic decision-making.