Cold Central Plant Recycling (CCPR) has been used by many state highway agencies to save material, money, time, and energy in pavement construction and rehabilitation. The objectives of this thesis were to: (1) perform an instrumented verification analysis, (2) evaluate the response and performance of two pavement configurations with a CCPR base layer through accelerated pavement testing (APT), and (3) construct models using mechanistic-empirical pavement design software for comparison with the APT results. The pavement configurations featured a 5-inch CCPR mixture with either a 3-inch or 1.5-inch SM-9.5D surface mixture. Each section was instrumented with strain gauges, pressure cells, and thermocouples. A heavy vehicle simulator (HVS) was used to load three replicate test sections in each lane, with the temperature controlled at 39°C at a depth of 1.5 inches. Results from the instrument verification analysis showed that the strain gauges and pressure cells used in the experiment recorded pavement responses with a high degree of repeatability. In addition, the loading condition variables (speed, wheel load, and tire inflation pressure) affected the response following the expected trends and did not affect the repeatability of the instruments. The average CV of all strain gauge and pressure cell signals was approximately 0.009 or 0.9%, and 0.004 or 0.4%, respectively. In terms of the rutting comparison, the sections with the 3-inch surface layer outperformed the sections with the thinner 1.5-inch surface layer. However, the age of the pavement at the start of testing significantly affected the rutting performance. After adjusting for the pavement age at the time of testing, the section with the thicker surface showed approximately half of the rutting of the section with the thinner surface. The results from preliminary ME Design analysis indicate that the software cannot model the studied APT sections using the default material properties and calibration factors available at the time of analysis. In particular, the software does not seem to be prepared to model the CCPR materials. / Master of Science