Introduction In this study, we investigate whether the addition of biomarkers to a model based on traditional risk factors improves risk prediction and patient selection for revascularization in atherosclerotic renovascular disease. Methods Patients in the Salford Renovascular Study who had the following biomarkers analysed on a baseline sample were included in this study: FGF-23, Cystatin C, kidney injury molecule-1, myeloperoxidase, neutrophil gelatinase-associated lipocalin, N-terminal prohormone of brain natriuretic peptide (NT-proBNP), high-sensitivity Troponin T and anti-apolipoprotein A1 IgG. Cox proportional hazards models and net reclassification index were used to study the effects of either individual or a panel of biomarkers on predicting death, end-stage kidney disease and cardiovascular events. Results A total of 112 patients were followed up for a median 59.9 months (IQR 33.6–86.9). In total, 75 patients died, 21 reached end-stage kidney disease and 36 suffered a cardiovascular event. Only NT-proBNP maintained a statistically significant association with all end-points (death: HR 1.62 [95% CI 1.26–2.10], P < 0.0005; end-stage kidney disease: HR 1.51 [95% 1.19–1.91], P = 0.001; cardiovascular event: HR 1.56 [95% CI 1.23–1.97], P < 0.0005). Risk reclassification improved with addition of all biomarkers as a panel to the base model. Only patients with NT-proBNP concentrations above 300 ng/L gained benefit from revascularization with regard to all adverse end-points compared with medically managed patients. Conclusions NT-proBNP is independently associated with increased risk for all adverse events in atherosclerotic renovascular disease. Novel biomarkers may have an incremental risk predictive value when used in combination with traditional risk factors, and NT-proBNP may have value in patient selection for revascularization. Given the small size of this study, larger multicentre studies are required to validate these findings.