Abstract Background Dry eye disease (DED) is heterogeneous, and patient-reported symptoms frequently do not correspond to objective ocular surface signs. This study evaluated symptom–sign discordance in patients with DED and characterized discordant clinical phenotypes using an age-aware ocular surface analysis. Methods This retrospective cross-sectional study included 120 patients with dry eye symptoms. Participants completed the Ocular Surface Disease Index (OSDI) and 5-item Dry Eye Questionnaire (DEQ-5). Ocular surface evaluation included tear breakup time (TBUT), tear meniscus height (TMH), Schirmer I testing, Oxford staining, meibography-derived meibomian gland loss, and meibomian gland function assessment. Patients were classified into four symptom–sign phenotypes. Because several objective variables were used to define sign status, they were interpreted as phenotype-related clinical characteristics rather than independent predictors. Age-adjusted analyses were performed to account for the confounding effect of age. Results The mean age was 48.6 ± 13.2 years, and 78 patients (65.0%) were female. Symptom–sign discordance was observed in 50 patients (41.7%): 28 (23.3%) had a high-symptom/low-sign phenotype and 22 (18.4%) had a low-symptom/high-sign phenotype. OSDI showed weak-to-moderate correlations with TBUT, TMH, and meibomian gland loss. In unadjusted comparisons, the high-symptom/low-sign group had higher meibum quality and expressibility scores, whereas the low-symptom/high-sign group had greater meibomian gland loss and older age. After age adjustment, meibum quality (p = 0.011) and expressibility (p = 0.019) remained significantly different among phenotypes, whereas meibomian gland loss was attenuated and no longer statistically significant (p = 0.071). Conclusions Symptom–sign discordance is common in DED. Functional meibomian gland impairment may contribute to high symptom burden despite relatively mild conventional signs, whereas structural gland loss in low-symptom/high-sign patients may be partly age-related. A multimodal, age-aware ocular surface assessment may improve clinical interpretation of dry eye phenotypes.