Purpose Current staging guidelines are inadequate in predicting survival outcomes and recurrence after chemoradiotherapy (CRT) for ASCC. The objective of our study is to identify prognostic factors, particularly p16 as a predictive biomarker to improve risk stratification beyond routine clinicopathological parameters. We aim to establish nomograms to predict the survival outcomes post CRT. Methodology The prospective maintained ASCC database at Peter MacCallum was interrogated to identify risk factors that are associated to survival outcome. Prediction nomograms were constructed using independent prognostic factors after a Cox Proportional regression analysis for 1-, 3-,5- and 10-year OS, DFS, LRFS and DMFS. Model calibration and internal validation with bootstrapping were undertaken to assess for discrimination. Results 654 patients received curative intent CRT over a median follow up of 57 months. 5-year OS, DFS, LRFS and DMFS were 77%, 75%, 81% and 85% respectively. Univariate and multivariate analyses identified age, sex, tumour stage, nodal and p16 status were significantly associated with worse OS, DFS, LRFS and DMFS. Our nomographs show excellent discrimination with Harrell Concordance Indices of 0.707 for OS, 0.727 for DFS, 0.738 for LRFS and 0.7563 for DMFS accordingly. Specifically, the absence of p16 expression remains a significant poor predictor of survival in all nomograms. Conclusion Increased age, male sex, advanced tumour, nodal positivity and p16 negative status were significant variables associated with worse survival outcomes. Nomograms generated from this study were able to accurately predict clinical outcomes and can be an invaluable clinical tool for personalised risk estimation.