BACKGROUND: Little evidence is available to determine which patients should undergo repeat biopsy after initial benign extended core biopsy (ECB). Attempts have been made to reduce the frequency of negative repeat biopsies using PSA kinetics, density, free-to-total ratios and Kattan's nomogram, to identify men more likely to harbour cancer but no single tool accurately predicts biopsy outcome. The objective of this study was to develop a predictive nomogram to identify men more likely to have a cancer diagnosed on repeat prostate biopsy. METHODS: Patients with previous benign ECB undergoing repeat biopsy were identified from a database. Association between age, volume, stage, previous histology, PSA kinetics and positive repeat biopsy was analysed. Variables were entered stepwise into logistic regression models. A risk score giving the probability of positive repeat biopsy was estimated. The performance of this score was assessed using receiver characteristic (ROC) analysis. RESULTS: 110 repeat biopsies were performed in this period. Cancer was detected in 31% of repeat biopsies at Hospital (1) and 30% at Hospital (2). The most accurate predictive model combined age, PSA, PSA velocity, free-to-total PSA ratio, prostate volume and digital rectal examination (DRE) findings. The risk model performed well in an independent sample, area under the curve (AUCROC) was 0.818 (95% CI 0.707 to 0.929) for the risk model and 0.696 (95% CI 0.472 to 0.921) for the validation model. It was calculated that using a threshold risk score of > 0.2 to identify high risk individuals would reduce repeat biopsies by 39% while identifying 90% of the men with prostate cancer. CONCLUSION: An accurate multi-variable predictive tool to determine the risk of positive repeat prostate biopsy is presented. This can be used by urologists in an outpatient setting to aid decision-making for men with prior benign histology for whom a repeat biopsy is being considered.