The stable development of society is inseparable from the high-level developments of manufacturing industry. Production is the key point of manufacturing industry， and the long-term sustainable and stable output depends on the stable operation of industrial equipment systems. The production stoppage caused by systems’ failure will be bound to the economic loss. How to find the equipment system’s failure to avoid the economic loss as soon as possible has become a hotspot in the current application research. The traditional method of regular manual inspection not only increases the production cost， but also delays the finding of problems and fails to achieve the real-time monitoring purpose. Besides， with the rapid developments of information technology， the monitoring of equipment systems has become increasingly intelligent. Using the historical data of the equipment system to detect its status is a more agile and more efficient way to find the “sub-health” problems during operation. It can provide beneficial decision support for equipment administrators. Data of the remaining useful life （RUL） prediction of the equipments can provide efficient and intelligent solutions， and has broad application prospects in the industrial field. Therefore， we focus on the research progress of the RUL prediction technology for the equipment systems in recent years. We summarize studies on RUL， and discuss the advantages and disadvantages of the RUL prediction’s theories and methods. Finally， we identify the future research direction and development trend of the RUL prediction technology for equipment systems.