<p>Prognostics and health management (PHM) is paving the way for efficient and reliable maintenance strategies in operating systems and industries. PHM provides a systematic approach to accurately identify health degradation and forecast the RUL. Applying PHM to mobility batteries can enhance battery maintenance and ensure the safe operational life of mobility systems. Different PHM techniques built on the model- and data-driven approaches have been abundantly used by researchers for mobility batteries. An inclusive understanding of both model- and data-driven methods is essential to develop a systematic PHM workflow for mobility batteries. This review serves that need by offering a detailed analysis of the various PHM approaches employed in mobility batteries. In contrast to existing review papers that have focused on limited aspects of PHM, this work aims to cover the PHM workflow comprehensively in mobility batteries. This work includes detailed information about the battery degradation mechanism and key PHM workflow concepts. Different model- and data-driven approaches are covered comprehensively, along with battery health monitoring systems and prognostics practices. By covering the vital aspects of mobility battery degradation as well as various PHM approaches, this paper fills a significant gap in existing works. It provides researchers and practitioners with a thorough road map for creating PHM systems for mobility batteries. This review makes a significant contribution to the subject with its critical observations and in-depth analysis. It opens the door for more developments in battery management and maintenance and offers valuable insights into developing an efficient PHM workflow.</p>