The pharmacokinetics of Tacrolimus is characterized by a high interindividual variability that is mainly explained by pharmacogenetics biomarkers. The aims were to develop a population pharmacokinetic model (Pk pop) taking into account post-transplant phases (PTP), CYP3A4*1B, CYP3A4*22 and CYP3A5*3 polymorphisms on Tac pharmacokinetics in adult kidney transplant patients. The Pk pop study was performed using a nonparametric approach (Pmetrics*). The influence of covariates (age, weight, sex, hematocrit and CYP3A4*1B, CYP3A4*22 and CYP3A5*3 polymorphisms) was tested on the model's Pk parameters. The performance of the final model was assessed using an external dataset. A one-compartment model (Vd: volume of distribution, CL: Tac Clearance) was found to correctly describe the evolution of the C0/D regardless of the PTP. The influence of the covariates has shown that only the CYP3A4*1B and CYP3A4*22 polymorphisms were significantly associated only with CL, regardless of PTP (p = .04 and 0.02, respectively). Only the CYP3A4*22 polymorphism influenced CL during early PTP (P1: the first three months, p = .02). During the late PTP (P2: >3 months), only CYP3A4 polymorphisms were found to affect CL (p = .03 for both). The external validation of the final model, including both CYP3A4 polymorphisms, showed an acceptable predictive performance during P1 and P2. We developed and validated a tac Pk pop model including both CYP3A4*22 and CYP3A4*1B polymorphisms, taking into account PTP. This model was very useful in the Tac dose proposal in this population on any PT day but could not be used in other organ transplants due to pharmacokinetic differences.