Crystal morphology prediction tools have drawn scientific and industrial interest because of the important relationship between the morphology and crystal properties and performance. Existing multiscale models consider the behavior of growth units at the microscale to inform macroscale predictions and are continually improving. Typically, these mechanistic models employ microkinetic rate expressions to calculate step velocities and consequently determine face growth rates, which allow for morphology predictions. Surface-level kinetic Monte Carlo (kMC) simulations provide an alternate route to obtain step velocities by simulating the dynamics of crystal steps. In this article, we apply kMC simulations to predict the crystal morphologies of various centrosymmetric molecules, including rubrene, olanzapine, and adipic acid. We compare our predictions to experimental crystal habits from the literature and address potential reasons for discrepancies.