The Lithium (Li) Metal Battery (LMB) has shown promise in overcoming the energy storage limitations of the Lithium Ion Battery (LIB) due to the high theoretical capacity of the Li Metal anode. However, it is hindered by an unstable interface and uncontrolled dendrite growth leading to a decrease in coulombic efficiency and safety concerns. While it is difficult to study the electrode-electrolyte interface operando, computational methods can be used to resolve the interface and track the complex physical and chemical phenomena at this location. Specifically, we can use computational modeling to better understand the morphological evolution of deposited Li starting from the nucleation of Li through the growth of the dendrite. In this work we propose a computational method that combines nucleation physics, deposition, and ion transport to study how surface energy and defects impact Li deposition. It is observed that when defects increase the surface energy the nucleation rate decreases resulting in less dendritic growth and more homogenous plating.