Automated pavement data collection technologies have gained momentum due to the fact that the automated data have more detail, greater quantity, better quality, and better repeatability. A systematic method of developing performance and distress models; however, is lacking. This study was conducted to address this issue. Maximum Allowable Extent (MAE) values and the Analytical Hierarchy Process (AHP) were used to calculate composite distress and performance indices. Non-linear sigmoidal distress and performance models were then developed. A visual comparison of the automated model curves and the corresponding windshield model curves indicated that the automated models are robust. In addition, trigger points on the North Carolina Department of Transportation (NCDOT) Pavement Management System (PMS) decision tress were determined, which allow NCDOT engineers to select appropriate maintenance actions.