Disclosed is a prediction method of glomerular filtration rate (GFR) from urine samples after kidney transplantation to provide an information needed for predict renal function after the transplantation, more particularly to a prediction method of glomerular filtration rate (GFR) from urine samples after kidney transplantation, which comprises detecting metabolic profiles of five biomarkers, 5a-androst-3-en-17-one (AS), glycocholic acid (GC), sphingosine (SG), tryptophan (TR) and histidine (HT), from urine samples of patients. Glomerular filtration rate (GFR) after kidney transplantation can be predicted more rapidly and precisely to provide an information needed for predict renal function after the transplantation by using five metabolites as biomarkers. The method provides more specific, sensitive, and reliable biomarkers that monitor clinical outcomes and adverse renal events after kidney transplantation, such as rejection, drug toxicity, delayed graft function, and infection.