The invention discloses a rotating machinery remaining life prediction method based on FDA and SVDD. The method is characterized by converting collected discrete data into a smooth function through a functional data analysis (FDA) method to solve the problems of information loss or model estimation distortion and the like, identifying machinery operation state through SVDD to reduce sample collection requirement and provide predication accuracy, and calculating radius of an SVDD model of a test sample and comparing the radius with a full life cycle time radius track to obtain a predication result. The method effectively reduces sample collection time required in predication of the remaining life of rotating machinery, and improves prediction accuracy.