Head and neck squamous cell carcinoma (HNSCC) typically presents unfavorable prognostic outcomes. Telomere dysfunction is involved in malignant transformation and tumor development processes. We performed a comprehensive array of analyzes to assess and authenticate the prognostic significance of telomeres in HNSCC, including the identification and examination of differential telomere maintenance genes (TMGs) with prognostic significance, Cox regression analysis, survival analysis, nomogram prediction, time receiver operating characteristic (ROC) analysis, Immune characteristics, enrichment analysis, drug sensitivity analysis, Mendelian randomization (MR) analysis, and real-time quantitative PCR (qRT-PCR). Employing bioinformatics, we derived a prognostic model comprising 80 significantly differentially expressed genes (DEGs) of prognostic relevance. Subsequent analysis using the HPA database revealed 24 genes, and they were identified to exhibit elevated expression levels in tumor patients. The model predicted an area under the ROC curve (AUC) of 0.973 for the 1-year survival rates of patients with HNSCC. The high- and low-risk groups exhibited different immune statuses and drug sensitivities. More precisely, HNSCC individuals in high-risk groups were more prone to show a favorable response to 17 chemotherapeutic drugs. Additionally, our result of qRT-PCR was also consistent with the analysis. The prognostic model centered on differential TMGs shows great potential as a valuable tool for risk stratification, predicting survival outcomes, assessing immune status, screening potential drugs, and exploring genetic associations with HNSCC.