The remaining useful life of components is crucial in maintenance planning. However, it is difficult to determine whether or not a model is reliable and trustworthy. There is no clear instruction about how to evaluate a remaining useful life prediction model since the output results are not displayed in the physical system. Furthermore, the models may generate an inaccurate prediction due to missing or outlier data. The idea of resilience is presented to evaluate the performance of the remaining useful life prediction model in order to increase model dependability and robustness. This study offers a definition for the resiliency of remaining useful life prediction models. The study then provides methods for evaluating the models used for the remaining useful life prediction. The work could serve as a springboard for further research into topics such as resilience and life prediction models.