Due to increased screening, the majority of patients are diagnosed at early-stage breast cancer. It is essential therefore to be able to more accurately predict the risk of recurrence and distant metastasis for the management and prediction of breast cancer progression. Clinicopathological parameters, specifically nodal status, tumor size and hormonal receptor status are routinely used for the identification of women at high risk of recurrence. However, these parameters alone and prognostic scores based on clinical variables have limited predictive value for late metastasis risk in patients with early breast cancer. Emerging techniques using gene expression-based approaches show great promise in improving prognostic and predictive accuracy. Nevertheless, these multi-gene/molecular scores present discordant results when used for risk assessment. Therefore, there is an urgent clinical need to identify novel predictive and prognostic biomarkers for discriminating high- and low-risk patients. In this review we focus on recent data implicating the use of clinicopathological parameters, serum biomarkers, and multi-gene profiling scores for the prediction of late recurrence and distant metastasis in early-stage breast cancer.