Diabetic Nephropathy (DN) is the deleterious effect of diabetes mellitus on renal structure, or a function caused by it. The rate of rise in, serum creatinine is observed for the progression of DN. Retrospective data is collected from 132 patients. As 60 patients form uncensored cases, remaining 72 patients are censored cases. In this paper we have developed three models. The first model is based only on uncensored cases with left truncation. The second model also includes censored data. Fisher's information matrix has been applied to find variances and asymptotic confidence interval for the estimated parameters. The method of maximum likelihood is used to estimate unknown parameters in both the models. In the last model, onset times are arranged as to estimate mean onset time of DN for all the patients by using application of order statistic. We aim to predict onset time of DN for new diabetic patients.