Tacrolimus is the key component of most contemporary immunosuppressive drug regimens for the prevention of transplant rejection. Area under the concentration time curve over 24 h (AUC ) predicts efficacy, but predose (trough) tacrolimus blood concentration (C ) is currently used to guide dosing. In clinical or research situations where an estimate of AUC is required, collection of a full 24 h pharmacokinetic (PK) profile is cumbersome. Limited sampling strategies (LSSs) have been developed for some tacrolimus preparations but not for the new, extended-release, once-daily formulation of tacrolimus, ENVARSUS XR. Twenty-four kidney transplant recipients were enrolled in this study. Twenty-four tacrolimus PK profiles were obtained over 24 h. Multiple linear regression was used to generate LSSs with the best subset selection for accurate estimation of tacrolimus AUC . The predictive performance of each model was assessed in the evaluation group. The correlation between actual and predicted AUC was evaluated and mean percentage prediction error (MPE%), mean absolute percentage prediction error (MAE%), and root mean squared error (RMSE) were calculated for each prediction model to assess bias and precision. The selected LSSs were highly correlated to AUC compared with the correlation between C and AUC . Two and three sampling points limited sampling strategies: C , C , and C provide the most reliable and effective LSS for estimation of tacrolimus AUC in routine clinic use. These limited sampling models can be applied in therapeutic drug monitoring schemes to personalize tacrolimus dosing for kidney transplant recipients on treatment with extended-release tacrolimus.