An integrated Case Based Reasoning model is proposed to predict the endpoint temperature of molten steel in AOD. Case's problem part is represented by a set of feature attributes and a set of state attributes. The boundary value of state attributes can be obtained by M5P. Case similarity is computed based on Grey Relational Degree with different weights of attributes in order to solve the problem of obtaining the accurate results with incomplete information. Entropy Weight Method is adopted to determine the weights of attributes. A two-step case retrieval, composed of rough search and delicate search, is pro-