Prediction of the effective number of full charging-discharging cycle is valuable for lithium-ion battery (LIB) replacement and recycling. This paper proposes to construct a cumulative degradation indicator (CDI) to work as a more predictable indicator. The proposed CDI is better than the original degradation indicator (DI) in multiple criteria. In the stage of determining the end-of-life (EoL) threshold, a relevance vector machine (RVM) is introduced to screen a small number of available samples, and to reduce the prediction error. In the experimental verification stage, this paper uses LIB full-life data from NASA to verify the early and long-term prediction performance of RCDC using a small sample. The experimental results show that when the proportion of training data approaches 50%, the prediction error gradually converges to the actual value.