Computational fluid dynamics (CFD) is a powerful simulation tool that was successfully used to investigate mixing, turbulence, and shear in a laboratory-scale MSMPR and batch cooling crystallizer for an organic fine chemical. CFD gives a qualitative engineering insight into the effects of the impeller configuration on the crystallization rates and particle size distribution. A process-modelling tool, gPROMS (Process Systems Enterprise), was used to model particle size and size distribution in both batch and continuous laboratory-scale crystallization processes with predictive simulations in good agreement with experimental results. CFD simulations of large-scale crystallizations using constant specific power input per unit mass, predict an increase in macromixing and decrease in micromixing and turbulence. This effect should improve process performance of batch cooling crystallizers on scale-up including the product quality of the final solid form in terms of the particle size and crystal habit. This is due to improved suspension mixing and secondary nucleation effects and attrition decreasing with scale-up. CFD heat transfer simulations, however, predict varying temperature profiles together with less efficient heat transfer with the presence of distinct cooling zones, which can degrade product performance in terms of encrustation and agglomeration resulting in wider particle size distributions.