The rapid development of infrastructure has led to various environmental, economic, and societal challenges. The pavement industry, in particular, is known for its high energy consumption, resource utilization, and pollution generation. Despite recent efforts to augment the sustainability and circularity of pavement infrastructure, there remains a lack of comprehensive assessment methods to evaluate the existing practices and technological advancements, which makes the implementation of innovations challenging. This study reviewed twelve existing circular economy indicators and frameworks to understand the challenges associated with their use in evaluating pavement infrastructure. The indicators included Material Circularity Indicator (MCI), Circular Economy Index (CEI), CB’23 framework, Environmental Sustainability and Circularity Indicator (ESCi), Circular Economy Indicator Prototype (CEIP), Material Reutilization Score (MRS), Value-based Resource Efficiency (VRE), Circular Economy Performance Indicator (CPI), Recyclability Benefit Rate (RBR), Reuse Potential Indicator (RPI), Product-level Circularity Metric (PLCM), and Building Circularity Indicator (BCI). These indicators cover different aspects of circularity and sustainability, such as resource efficiency, material circularity, product’s lifetime, preservation of product’s functions, and environmental and economic impacts. However, none of the indicators provide a comprehensive assessment tailored for pavements, encompassing circularity and all three aspects of sustainability. Considering factors such as data availability, overlap of conceptual and methodological approach, and the scope covered, six of the twelve circularity indicators were evaluated in this study, namely, MCI, CEI, CB’23, ESCi, CEIP, and MRS. Since these indicators were not originally developed to assess pavements, appropriate methodological modifications were proposed and validated using three different pavement construction and maintenance methods that are commonly adopted in the Netherlands. In order to map the road to sustainability, the analysis was complemented with the Environmental Cost Indicator (ECI, or in Dutch, MKI) and Net Present Value (NPV). The three case studies adopted in this study included: (a) resurfacing the pavement once in every 12 years with 25% Reclaimed Asphalt Pavement (RAP), hereafter referred as Business As Usual (BAU) scenario, (b) life-extension maintenance by rejuvenating the pavement in years 5 and 10 since construction followed by resurfacing, and (c) use of low-emission technology, i.e., Warm-Mix Asphalt (WMA) with higher RAP 3 percentage (50% by mass) in the mix. An analysis period of 36 years was chosen as per the Federal Highway Administration guidelines and the foreground data was collected from roadway stakeholders. Additional missing information was also gathered from Dutch asphalt product category rule, international databases, and existing literature. The results revealed the strengths and limitations of each indicator. MCI being a mass- based indicator captured the material circularity and product’s service life but failed to represent the environmental and economic impacts. Although CEI indirectly captures the environmental impacts as it is governed by market prices, which takes into consideration the societal and environmental taxes, it is volatile as it is can also be influenced by the supply and demand of raw materials and material quality, potentially overlooking the benefits of using higher percentages of recycled materials. CB’23 provides detailed information by classifying pavement components across different circular economy principles, which aids in targeted improvements but complicates the comparison of alternatives as a whole. ESCi combines MCI and MKI to incorporate circularity and environmental sustainability but requires extensive modelling and lacks economic and social considerations. CEIP, as a questionnaire-based indicator, covers a wide range of circularity principles, but the weighting and scoring of questions is subjective as it is based on the expert opinion leading to concerns of bias in decision making. MRS involves simplified mathematical computations, thereby serving as an attractive choice for quick decision-making. However, it is fundamentally biased to cover only the recycling strategy, and ignores the aspect of lifecycle use, thereby not accounting for durability of the asset. With regards to the case studies, MKI, MCI, ESCi, and MRS indicate that the WMA alternative was the most circular strategy. LCCA, CEI, and CEIP favour the rejuvenation alternative, while CB’23 may favour one alternative when the result of one sub-indicator is designated to be the criterion for decision making. However, since all the indicators cover different aspects of circularity, it is important to complement the results with environmental, economic, and social sustainability indicators for comprehensive and robust assessments. In practice, choosing different alternatives based on the selected indicators can lead to varying end result. Therefore, it is essential to handle these implications carefully and the scope, boundaries, methods, assumptions and any limitations must be clearly stated for transparent decision-making. Future research should focus on improving data quality and developing methods to integrate social sustainability, wherever feasible.