Recent studies have shown that many immune-related long non-coding RNA (lncRNA) has unique advantages as a novel biomarker in cancer diagnosis, treatment and prognosis. The study of immune-related lncRNAs in head and neck squamous carcinoma (HNSCC) is of great importance. Based on gene expression data and clinical data of HNSCC patients, immune-related lncRNAs with prognostic value were identified using univariate Cox regression analysis, Lasso regression analysis and multivariate Cox analysis to construct a prognostic risk score model. And the performance of the prognostic model was also evaluated using Kaplan-Meier analysis and time-dependent ROC curves. The results were screened to obtain 7 key lncRNAs and constructed survival prognostic models. Kaplan-Meier analysis revealed that the survival rate of the high-risk group was significantly lower than that of the low-risk group, while the ROC curve proved that the model has good predictive ability. The results of the study showed that the survival prognostic model constructed based on seven immune-related lncRNAs could provide effective survival prognosis prediction for HNSCC patients.