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Understanding the morphology and spatial orientation of microstructures is essential for predicting and optimizing the macroscopic behavior of advanced steels. In this study, we present a unified framework for microstructural characterization that combines experimental analysis with phase-field simulations. On the experimental side, two-point spatial correlation analysis of EBSD-derived microstructures was employed to quantify variant morphology, thickness and spacing, establishing a robust baseline for validating computational predictions. Complementing this, three-dimensional phase-field simulations were carried out under applied strains representative of press hardening conditions. Two-dimensional image analysis enabled the extraction of conventional morphological descriptors such as area, length, thickness, aspect ratio, compactness and eccentricity from cross-sections, while three-dimensional statistical measures based on 2-point statistics quantified spatial correlations, anisotropic growth and variant alignment across the simulated volume. The combination of conventional descriptors with statistical correlations provides a multiscale and multidimensional perspective on the evolution of bainitic microstructures. This integrated approach advances the understanding of complex morphological anisotropy, strengthens process–structure relationships and establishes a foundation for data-driven design of high-performance steels subjected to thermo-mechanical conditions.