Laryngeal squamous cell carcinoma (LSCC) is a common malignant tumor of the head and neck that significantly impacts patients' quality of life, with chemotherapy resistance notably affecting prognosis. This study aims to identify prognostic biomarkers to optimize treatment strategies for LSCC. Using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), combined with mitochondrial gene database analysis, we identified mitochondrial lncRNAs associated with drug resistance genes. Key long non-coding RNAs (lncRNAs) were selected through univariate Cox regression and Lasso regression, and a multivariate Cox regression model was constructed to predict prognosis. We further analyzed the differences in immune function and biological pathway enrichment between high- and low-risk groups, developed a nomogram, and compared drug sensitivity. Results showed that the prognostic model based on seven mitochondrial lncRNAs could serve as an independent prognostic factor, with Area Under the Curve (AUC) values of 0.746, 0.827, and 0.771 at 1, 3, and 5 years, respectively, outperforming some existing models, demonstrating high predictive performance. Significant differences were observed in immune function and drug sensitivity between the high- and low-risk groups. The risk prediction model incorporating seven drug resistance-related mitochondrial lncRNAs can accurately and independently predict the prognosis of LSCC patients.