Prognostics research has attracted much attention due to its wide range of application objects, advanced technical theories and high practical value. Therefore, from the perspective of “literature tracking”, we try to mine and analyze the knowledge structure, distribution context and research hotspots of prognostics, which would be a new attempt to the research of prognostics review. The results show that: 1)In terms of knowledge structure, prognostics has strong coupling correlation with condition monitoring and health management. Model driven, knowledge driven, statistical driven, probabilistic reasoning methods, machine learning and deep learning are the key technical categories of prognostics. 2)In terms of hotspots migration, the research on prognostics mainly includes four periods: theoretical foundation period, connotation extension period, technology emergence period and method integration period. This paper summarizes the current achievements, difficulties faced and development contributions, clarifies the development track and practical effect of the prognostics theory, and provides a clear direction for the step development of prognostics in the future, which can improve the quality of collected big data, online prediction and migration learning.