The key to understanding why thermodynamics alone cannot determine crystallization outcomes is related to the fact that crystallization from an out-of-equilibrium solution is dominated by kinetic factors that are sensitive to changes in the reaction environment. Both of the mechanistic steps necessary for crystallization to occur in metastable solutions-namely, the formation of a crystal embryo (nucleation) and its subsequent growth into a bulk phase-are determined by the dynamics and frequency of transfer of building blocks from the solution to the crystal. As such, the choice of solvent, temperature and solute concentration, in particular, can change the polymorphic outcome of precipitation. Because the dynamics of the building blocks assembly discussed above are so important, molecular dynamics (MD) is typically the simulation tool of choice to investigate the crystallization of molecular and ionic solids in silico. Through the lens of statistical mechanics, MD simulations unlock both thermodynamic and kinetic information by tracing the motion of up to 10 9 atoms over simulation times ranging from 10 -9 to 10 -6 s. Nevertheless, understanding and predicting how crystals with well-defined composition, structure and properties assemble from a supersaturated solution remains a formidable task. The small time scales probed by MD simulations are generally inadequate for studying the complex microscopic steps involved in crystal nucleation and growth. As we highlight below, however, advanced sampling schemes and theoretical treatments can circumvent these limitations. In doing so, MD simulations can help to determine crystal nucleation and growth rates, polymorphism, crystal habit and defect density as a function of solution composition, temperature and the presence of additive/impurities and external forces. Indeed, a wealth of information can be gained by combining complementary computational tools with studying different aspects of crystallisation from solution, but it is not always apparent which tools are most appropriate for the specific task at hand.