As the world is moving towards electric vehicles , we are observing a wide use of Lithium-Ion batteries in modern transportation. Lithium-Ion Batteries offer several advantages over conventional battery systems, including higher energy density that is energy stored per unit mass, longer Cycle Life, faster Charging rates, low Self-Discharge, lighter weight, and ease of maintenance as the memory effect present in other batteries is absent . Of course, challenges remain, e.g. accurate battery State of Health (SOH) estimation which stays as an indispensable parameter for safety and useability. Inaccurate SOH estimation can lead to unexpected vehicle behavior and a degraded end-user experience, especially due to incorrect "distance to empty" predictions. Also, different battery chemistries present various challenges, creating need of tailored models. In this paper, different SOH estimation techniques are reviewed and compared in detail . The SOH estimation approaches are broadly classified