Radiotherapy (RT) is of critical importance in the locoregional management of early breast cancer. Over 50% of patients receive RT at some time during the treatment of their disease, equating to over 500 000 patients worldwide receiving RT each year. Unfortunately, not all patients derive therapeutic benefit and some breast cancers are resistant to treatment, as evidenced by distant metastatic spread and local recurrence. Prediction of individual responses to RT may allow a stratified approach to this treatment permitting those patients with radioresistant tumours to receive higher doses of RT (total and/or tumour cavity boost doses) and/or radiosensitising agents to optimise treatment. Also, for those patients unlikely to respond at all, it would prevent harmful side effects occurring for no therapeutic gain. More selective targeting would better direct National Health Service resources, ease the burden on heavily used treatment RT machines and reduce the economic cost of cancer treatment. Unfortunately, there are no robust and validated biomarkers for predicting RT outcome. We review the available literature to determine whether classification of breast cancers according to their molecular profile may be used to predict successful response to, or increased morbidity from, RT. Class-specific biomarkers for targeting by radiosensitising agents are also discussed.