Li-metal batteries, often heralded as the next frontier in energy storage technology, boast remarkable characteristics such as high energy density. Unlike traditional lithium-ion batteries, Li-metal batteries incorporate a lithium-metal anode, which significantly enhances their energy density. This higher energy density translates to a substantial increase in the amount of energy that can be stored in a given volume or weight, paving the way for more powerful and longer-lasting energy solutions[1–3]. However, significant shortcomings do exist, such as uneven Li-Metal deposition, dendrite formation, dead lithium, etc.[4] These phenomena are different than what are usually observed in Li-ion batteries with intercalation chemistry and lead to issues such as poor cycle life, low coulumbic efficiency, and safety concerns.[3]Mathematical modeling is a promising approach to studying the physicochemical processes involved in the Li-metal batteries to understand the morphology changes during cycling. The plating and stripping of the lithium metal on the anode during cycling can be modeled as a moving boundary problem.[5] Since the process involves a shrinking and expanding electrolyte domain, moving boundary problems call for the fastidious implementation of the model equations and boundary conditions.[6]In this talk, we will show the general mathematical framework involved in modeling Li-metal batteries in 1D systems. It expands upon the importance of carefully implementing boundary conditions to tackle the mass conservation issue that arises while cycling the model. It will also touch upon the additional complexities associated with expanding the model to 2D systems with convection in the electrolyte phase.