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Objective The aim of this study was to construct a prognostic model of esophageal adenocarcinoma (EAC) based on immune-related long noncoding RNAs (immune-related lncRNAs) and identify prognostic biomarkers using the Cancer Genome Atlas (TCGA) database.Methods Whole genomic mRNA expression and clinical data of esophageal adenocarcinoma were obtained from the TCGA database. The software Strawberry Perl, R and R packets were used to identify the immune-related genes and lncRNAs of esophageal adenocarcinoma, and for data processing and analysis. The differentially expressed lncRNAs were detected while comparing esophageal adenocarcinoma and normal tissue samples. The key immune-related lncRNAs were screened using lasso regression analysis and univariate cox regression analysis, and used to construct the prognostic model using multivariate cox regression analysis. To evaluate the accuracy of the risk prognostic model, all esophageal adenocarcinomas were divided into high-risk and low-risk groups according to the median risk score, after which Kaplan-Meier (K-M) survival curves, operating characteristic (ROC) curve and independent prognostic analysis of clinical traits were created. In addition, statistically significant immune-related lncRNAs and potential prognostic biomarkers were identified using the prognostic model and multifactor cox regression analysis for k-m survival analysis. Results A total of 1322 differentially expressed immune-related lncRNAs were identified, 28 of which were associated with prognosis via univariate cox regression analysis. In addition, K-M survival analysis showed that the total survival time of the higher risk group was significantly shorter than that of the lower risk group (P = 1.063e?10). The area under the ROC curve of 5-year total survival rate was 0.90. The risk score showed independent prognostic risk for esophageal adenocarcinoma via single factor and multifactorial independent prognostic analyses. In addition, the HR and 95％ CI of each key immune-related lncRNA were calculated using multivariate Cox regression. Using k-m survival analysis, we found that 5 out of 12 key significant immune-related lncRNAs had independent prognostic value [AL136115.1 (P = 0.006), AC079684.1 (P = 0.008), AC07916394.1 (P = 0.0386), AC087620.1 (P = 0.041) and MIRLET7BHG (P =0.044)]. Conclusion The present study successfully constructed a prognostic model of esophageal adenocarcinoma based on the TCGA database, with moderate predictive accuracy. The model consisted of the expression level of 12 immune-related lncRNAs. Furthermore, the study identified one favorable prognostic biomarker, MIRLET7BHG, and four poor prognostic biomarkers (AL136115.1, AC079684.1, AC016394.1, and AC087620.1).