Diabetic kidney disease is diagnosed and staged by albuminuria and estimated glomerular filtration rate. Although albuminuria has strong predictive power for renal function decline, there is still variability in the rate of renal disease progression across individuals that are not fully captured by the level of albuminuria. Therefore, research focuses on discovering and validating additional biomarkers that improve risk stratification for future renal function decline and end-stage renal disease in patients with diabetes, on top of established biomarkers. Most studies address the value of single biomarkers to predict progressive renal disease and aim to understand the mechanisms that underlie accelerated renal function decline. Since diabetic kidney disease is a disease encompassing several pathophysiological processes, a combination of biomarkers may be more likely to improve risk prediction than a single biomarker. In this review, we provide an overview of studies on the use of multiple biomarkers and biomarker panels, appraise their study design, discuss methodological pitfalls and make recommendations for future biomarker panel studies.