The Falling Weight Deflectometer (FWD) is a nondestructive testing device employed by civil engineers to assess pavement structural conditions by simulating the load of moving heavy vehicles. The deflections measured through geophone sensors are used to calculate structural parameters for selecting appropriate maintenance strategies or managing road assets. However, at the network level, FWD testing faces challenges due to its time-consuming, stop-and-go operation, which makes it costly, especially when considering traffic control and safety on high-speed roads. The wide interval of FWD tests can lead to missed localized defects, while reducing the test intervals increases both time and cost. This issue is particularly acute in developing countries like Cambodia, where large-scale, frequent FWD surveys are financially and logistically challenging. This study proposes a framework for more efficient application of FWD by focusing on the identification of critical road sections and optimization of testing cycles rather than determining optimal testing intervals. To achieve the first objective, the authors apply the Fuzzy Analytic Hierarchy Process (FAHP) method to address a multi-criteria decision-making problem, using factors like International Roughness Index (IRI), initial FWD deflection, traffic loading, and rainfall. Instead of using a single snapshot of IRI, this study introduces a dynamic approach using the mixed Markov hazard (MMH) model to account for the deterioration progress of surface ride quality in terms of remaining pavement life. The criteria, rated using triangular fuzzy weights, provide a final defuzzified score to identify critical road sections prioritized for further FWD survey and maintenance interventions. Regarding the second objective, the study employs the MMH model to estimate deterioration rates over time, allowing for determining optimal FWD testing cycles that effectively balance the cost of testing with the risk of potential failures. The optimal FWD testing cycles can be categorized based on different levels of pavement structural design or initial bearing capacities. The case study identifies critical sections of double bituminous surface treatment (DBST) and asphalt concrete (AC) pavements, ensuring that resources are allocated to areas needing immediate attention and providing timely inspection. By prioritizing critical road sections and optimizing testing cycles, this study enhances the practicality and effectiveness of FWD application in Cambodia without conducting excessive testing across the entire road network.