Recently, lithium-ion batteries (LIBs) have become the leading energy storage solution for electric vehicles due to their high energy density and long lifespan. Examining the health condition of LIBs is essential for their safe and reliable operation. This paper thoroughly assesses the latest researches on techniques for forecasting the health of LIBs, examines the properties of diverse methodologies, and proposes future development directions. First, the aging mechanism of lithium-ion batteries is introduced and the factors affecting battery aging are explored. Then, based on different prediction objectives, the prediction of lithium-ion battery health is divided into state of health (SOH) estimation and end of life (EOL) prediction. The SOH estimation methods are introduced from model-based and data-driven methodologies, while the EOL prediction is focused on the data-driven methods. Finally, the future development direction of LIB health prediction is identified, and four new potential topics on battery prediction are proposed.