Frailty is an important risk factor for adverse events (AEs), especially in elderly patients. Therefore, assessing frailty before therapy is recommended. In head and neck squamous cell carcinoma (HNSCC) patients, frailty is prognostic for severe postoperative complications and declining quality of life (QoL) after HNSCC treatment. Thus, assessment of frailty may help to identify individuals at risk for AE caused by oncologic therapy. We investigated the relationship between frailty and symptom burden to better understand their interaction and impact on HNSCC patients. In this prospectively designed cross-sectional study, the presence of frailty and symptom burden was assessed by using the Geriatric 8 (G8) and Minimal Documentation System (MIDOS2) questionnaires. A total of 59 consecutively accrued patients with a first diagnosis of HNSCC before therapy were evaluated. Patients were considered frail at a total G8 score ≤ 14. The MIDOS2 symptom burden score was considered pathological with a total score ≥ 4 or any severe symptom (=3). Statistical correlations were analyzed using Spearman and Pearson correlation. Receiver operator characteristic (ROC) curves were used to analyze the potential of predicting frailty and MIDOS2. p-values < 0.05 were considered significant. A total of 41 patients (69.5%) were considered frail, and 27 patients (45.8%) had increased symptom burden. “Tiredness” was the most common (overall rate 57.8%) and “Pain” was the most often stated “severe” symptom (5 patients, 8.5%). G8 and MIDOS2 correlated significantly (ρ = −0.487, p < 0.001; r = −0.423, p < 0.001). Frailty can be predicted by MIDOS2 symptom score (AUC = 0.808, 95% CI 0.698–0.917, p < 0.001). Vice versa, the G8 score can predict pathological symptom burden according to MIDOS2 (AUC = 0.750, 95% CI 0.622–0.878, p < 0.001). Conclusions: The strong link between frailty and increased symptom burden assessed by G8 or MIDOS2 indicates a coherence of both risk factors in HNSCC patients. Considering at least one of both scores might improve the identification of individuals at risk and achieve higher QoL and reduced complication rates by decision making for appropriate therapy regimens.