In this study, we implemented for the first time the Population and Covariate Model (POPCOV) to simplify the Individual Treatment Planning (ITP) process in PRRT with minimal Physiologically based Pharmacokinetic (mPBPK) model. POPCOV method was used to predict the unknown parameters of the PBPK model using the individual covariates. Stepwise selection procedures (forward selection and backward elimination) were used for the covariate selection and the derivation of the final model. The performance of the final model was tested by comparing the predicted time-integrated activity coefficient (TIACs) from the Fixed-Dose Treatment Planning (FDP) i.e., mPBPK with mean parameters, and conventional ITP method, i.e., mPBPK with individual estimated parameters. Based on the POPCOV analysis, GFR was identified as the best covariate for the receptor density in the kidneys [Rk]. The final covariate model of receptor density in the kidney was: [Rk] (10-15mol/l) = 6.32x106∗(GFR/0.09)(0.67). These results indicated that the performance of POPCOV for ITP was around 12% better than the FDP and around 26% worse than the conventional ITP method for the kidneys. The results showed that the POPCOV method could be used as an alternative method in PRRT to predict kidneys TIACs in a case where the individual biokinetic data is unavailable.