Ministry of Transport (MOT) in the Kingdom of Saudi Arabia (KSA) is considering adopting the Mechanistic-Empirical Pavement Design method with its associated software the AASHTOWare Pavement ME Design (PMED) for its flexible pavements in the near future. The AASHTOWare PMED consists of distresses and international roughness index (IRI) prediction models that are nationally calibrated mainly using Long-Term Pavement Performance (LTPP) database in the United States. Implementing the AASHTOWare PMED in KSA requires two main tasks: 1. convert KSA data format to AASHTOWare PMED format, and 2. calibrate the distress and IRI models to KSA conditions. This study first prepared the KSA data to be accepted by AASHTOWare PMED and then calibrated the models to improve the pavement performance models predictions. After calibration, validation of these models was conducted to ensure accurate results with independent pavement sections. Goodness-of-fit statistics and null hypothesis test were used to assess each models’ prediction. Three flexible pavement models were successfully calibrated: asphalt concrete (AC) permanent deformation, top-down cracking, and IRI models. The results showed that the distress and IRI models with national (default) calibration are biased in predicating KSA pavements performance which required recalibration. Calibrating AC rutting, top-down cracking, and IRI models improved the prediction of KSA pavement performance. Most of the data used in this study were obtained from MOT. The AASHTOWare Pavement ME software (version 2.6.0) was used to complete the study.