Purpose: The objective of this study is to characterize the role of miRNAs in the classification of head and neck squamous cell carcinoma (HNSCC). Experimental Design: Here, we analyzed 562 HNSCC samples, 88 from a novel cohort and 474 from The Cancer Genome Atlas, using miRNA microarray and miRNA sequencing, respectively. Using an integrative correlations method followed by miRNA expression-based hierarchical clustering, we validated miRNA clusters across cohorts. Evaluation of clusters by logistic regression and gene ontology approaches revealed subtype-based clinical and biological characteristics. Results: We identified two independently validated and statistically significant (P < 0.01) tumor subtypes and named them “epithelial” and “stromal” based on associations with functional target gene ontology relating to differing stages of epithelial cell differentiation. miRNA-based subtypes were correlated with individual gene expression targets based on miRNA seed sequences, as well as with miRNA families and clusters including the miR-17 and miR-200 families. These correlated genes defined pathways relevant to normal squamous cell function and pathophysiology. miRNA clusters statistically associated with differential mutation patterns including higher proportions of TP53 mutations in the stromal class and higher NSD1 and HRAS mutation frequencies in the epithelial class. miRNA classes correlated with previously reported gene expression subtypes, clinical characteristics, and clinical outcomes in a multivariate Cox proportional hazards model with stromal patients demonstrating worse prognoses (HR, 1.5646; P ¼ 0.006). Conclusions: We report a reproducible classification of HNSCC based on miRNA that associates with known pathologically altered pathways and mutations of squamous tumors and is clinically relevant.