Aims:Prognostic models offer a precision approach to support clinical decision-making. Prior to clinical use, independent external validation is essential to demonstrate accuracy and generalisability across populations. We externally validated a Danish head&neck cancer outcome prediction model in an Australian cohort. Methods:Retrospective data from 502 patients treated at six centres were used to validate the multi-endpoint model, predicting 3year locoregional failure(LRF), distant metastases(DM) and death without evidence of disease(DeathNED). Model performance was assessed using Area Under Curve(AUC), calibration plots and subdistribution hazard ratios for competing risks. Model validation was also undertaken in patients ≥70yrs to examine model fairness in this subgroup. Results:3yr AUC values were 0.66(LRF), 0.73(DM) and 0.736(DeathNED) for the full cohort, with similar values obtained for the older subgroup. Subdistribution hazard ratios demonstrated the model could distinguish low (ref), intermediate, and high-risk groups for LRF (p<0.001) (HR 1.92; 95%CI:1.19-3.09; 4.69; 95%CI:2.79-7.88, respectively) and DM (p<0.001) (HR 2.34; 95%CI:1.07-5.14; 7.19; 95% CI:3.45-15.0). For DeathNED, there were significant differences between the risk groups (p=0.02). Significant separation was observed between low and high-risk groups (HR 2.40, 95% CI: 1.15-5.02), but not between low and intermediate-risk groups (HR 0.66; 95%CI:0.40-1.08). Calibration plots exhibited slight miscalibration in those at highest risk for LRF and DeathNED. Conclusions:The model demonstrated comparable performance in an Australian cohort relative to the Danish cohort. It may support personalised discussions around treatment decision-making, particularly for older patients who may need modified treatment due to frailty and comorbidities. It represents a step toward clinically deployable decision-support tools in radiation oncology. A clinician survey investigating potential clinical impact is underway