The utilization of atomically dispersed catalysts (ADCs) is renowned for its ability tomaximize metal efficiency and provide well-defined catalytic sites with increased uniformity. Although these advantages are commonly cited in the literature, a thorough investigation into the nature of these catalytic sites is imperative to comprehend their homogeneity and account for potential minority contributions. Typically, techniques such as scanning transmission electron microscopy (STEM) and x-ray absorption spectroscopy (XAS), along with additional methods like infrared spectroscopy (IR), are employed to study ADCs. While XAS is crucial for probing the local coordination environment, conventional analyses tools often yield averaged information rather than accurate specifics about these sites. Therefore, the development of methods that combine computational approaches with XAS becomes crucial for a comprehensive understanding of well-defined catalytic sites like ADCs, allowing for a more realistic assessment of their nature. This project addresses a significant knowledge gap within the XAS literature by aiming to bridge the gap between the computational catalysis and experimental XAS communities. The outcome of my Ph.D. thesis work, the development of the Quant- EXAFS method, serves as a significant contribution in bridging this gap. As the name suggests, QuantEXAFS is an automated tool designed for the quantitative analysis of EXAFS data, leveraging quantum chemistry tools such as density functional theory (DFT). This method was tested on various atomically dispersed catalysts, including platinum, and palladium supported on MgO, molybdenum, and platinum supported on zeolites (ZSM-5). Ongoing studies involve applying QuantEXAFS to analyze reduced samples of atomically dispersed catalysts. This method not only eliminates user bias from conventional EXAFS fitting, thereby adding robustness to the approach, but it also facilitates fitting multiple scattering paths to longer ranges in R-space. QuantEXAFS has proven instrumental in identifying the true nature of catalytic sites by attributing realistic structures to experimental observations. This valuable information can be fed back into reaction barrier calculations and compared with experimentally observed results, such as apparent activation energy. Moreover, QuantEXAFS extends its utility to quantify site heterogeneities in catalytic samples, we denote the name multi-site (MS) QuantEXAFS to this method. The incorporation of ab initio calculations into QuantEXAFS enables the theoretical calculation of Debye–Waller factors and facilitates their comparison. This enhancement contributes to the development of a comprehensive workflow for fitting EXAFS data, rendering it a more rigorous and accurate probe, particularly in the analysis of well-defined materials like atomically dispersed catalysts (ADCs).