Diabetic nephropathy is the main cause of morbidity and mortality in patients with Type 1 diabetes mellitus. Microalbuminuria has been established as a risk factor for the development and the progression of diabetic renal disease. A strong demand exists for better technologies to provide accurate diabetic nephropathy risk estimates before renal functional or structural disturbances already become established. Here, we present the application of a novel proteomics technology identifying urinary polypeptides and proteins. In this pilot study, we investigated 44 Type 1 diabetic patients with more than 5 years of diabetes duration compared with an age-matched control group. Random spot urine samples were examined utilizing high-resolution capillary electrophoresis (CE), coupled to mass spectrometry (MS). More than 1000 different polypeptides, characterized by their separation time and mass, were found between 800 Da and 66.5 kDa. Mathematical analysis revealed specific clusters of 54 polypeptides only found in Type 1 diabetic patients and an additional 88 polypeptides present or absent in patients with beginning nephropathy defined by the albumin-to-creatinine ratio (ACR; >35 mg/mmol). We observed polypeptide patterns characteristic for healthy controls and diabetic patients and subdivision of patients according to the excretion of polypeptides typical for diabetic nephropathy. Our study revealed that the urinary proteome contains a much greater variety of polypeptides than previously recognized and demonstrated the successful application of a novel high-throughput technology towards the human urinary proteome. Future prospective studies with the application of this technique may enable the earlier and more accurate detection of individuals at high risk to develop diabetic nephropathy.