The prevalence of type 2 diabetes is increasing at an alarming rate. Various complications are associated with type 2 diabetes, with diabetic nephropathy being the leading cause of renal failure among diabetics. In the present study, we developed a decision tree model integrating genetic and clinical features in a gender-based classification for the identification of diabetic nephropathy among type 2 diabetes patients. Clinical and genotyping data were obtained from a previous genetic association study involving 345 type 2 diabetic patients. The inclusion of genetic features and the implementation of an additional gender-based rule for classification yielded better prediction results. The current model supports the notion that genes and gender are contributing factors for the risk of diabetic nephropathy. Further refinement of the proposed approach has the potential to facilitate early identification of diabetic nephropathy and the development of more efficient treatment in a clinical setting.