The global shift towards sustainable energy solutions has made lithium-ion battery recycling essential for circular economy, handling resource efficiency, waste reduction, and industry innovation, aligning with SDGs #9 and #12. However, battery recycling plants are not yet at relevant scales, and transition to a circular battery value chain needs to be accelerated. To that end, a comprehensive computational framework is presented coupling CFD with PBM to simulate NiSO4·6H2O crystallization via antisolvent method for sustainable metal recovery in battery recycling applications. This integrated model solves discretized PBE to predict crystal size distribution in a continuous 3D T-mixer crystallizer, analyzing crystal formation and growth under steady state laminar flow (). A novel kinetic growth model is also developed experimentally to determine kinetic parameters, and is supported by precise Ni solubility data and nucleation thresholds, to ensure the occurrence of seeded crystal growth (desupersaturation). Crystal polymorphs are further characterized using powder XRD, confirming the formation of α − NiSO4·6H2O crystals. Influence of flow dynamics and residence time on seeded crystal growth and particle size distribution is investigated numerically. Impact of impinging flow on local supersaturation levels highlights the role of mixing in crystallization, revealing radial mixing intensification with Re. Increasing Re reduces mean crystal size owing to shorter residence times, leading to less supersaturation utilization. Moreover, PSD narrows with the increase in Re, and peak shifts towards smaller crystal sizes, while PSD broadens and shifts right along the mixing channel length. Eventually, the efficacy of T-mixer in promoting uniform crystal growth, targeting narrow PSD, is evaluated—enabling energy-efficient continuous crystallization systems. Furthermore, this predictive simulation approach will help in designing innovative crystallization processes, contributing to a truly circular economy.