Supporting the advancement of a low-carbon and sustainable society, trivalent chromium plating with improved current efficiency has emerged as a viable and environmentally friendly alternative to toxic hexavalent systems. Electrolytes based on concentrated CaCl₂ aqueous solutions provide high current efficiency and desirable deposit properties. Nevertheless, the coordination structure, complex distribution, and electrochemically active species under chloride-rich conditions remain inadequately understood. In this study, machine-learning potential molecular dynamics（MLP-MD）simulations were performed to elucidate chromium（III）speciation and diffusion behaviors in concentrated CaCl₂ aqueous solutions. The simulations revealed large fractions of multi-chloride anionic complexes such as ［CrCl₄（H₂O）₂］^－ and ［CrCl₅（H₂O）］^2－, in stark contrast to conventional equilibrium predictions dominated by the cationic species ［CrCl₂（H₂O）₄］^＋. This discrepancy underscores limitations of thermodynamic models derived from spectral analysis of compositionally non-identical systems. Moreover, this discrepancy highlights the value of non-empirical atomistic approaches for concentrated electrolytes. Furthermore, diffusion coefficients exhibit minimal dependence on complex valence, which suggests strong electrostatic screening in high-ionic-strength environments. These findings provide new insights into speciation and transport phenomena in trivalent chromium baths, establishing a theoretical foundation for optimizing sustainable electroplating processes.