Casein micelles are key structures in milk, influencing stability, nutritional properties, and functionality. Their hierarchical architecture, which is dynamic and responsive to environmental conditions, plays a crucial role in dairy processing. Understanding the structural and dynamic properties of casein micelles is essential for optimizing dairy products and processing techniques. This study presents a novel method for characterizing and evaluating casein micelles using a combination of Asymmetrical Flow Field-Flow Fractionation (AF4) and Small-Angle X-ray Scattering (SAXS) at synchrotron facilities. By coupling AF4 with SAXS, we can fractionate milk samples according to micelle size and gain insights into their structural organization. However, the high-throughput data generated in such experiments pose challenges for traditional data analysis. We introduce an automated data processing pipeline utilizing the McSAS software in combination with Indirect Fourier Transformation, allowing for efficient fitting of SAXS data and extraction of structural parameters such as radius of gyration (Rg) and maximum particle dimension (Dmax). This integrated approach provides a more detailed understanding of the heterogeneity and structural dynamics of casein micelles, revealing distinct features of their size distribution, internal cavities, and overall micelle structure across different fractions. The method offers a powerful tool for future investigations into the behavior of casein micelles under varying environmental conditions, with potential applications in optimizing dairy product formulations and studying casein micelle dynamics.