In order to improve the performance of face recognition system based on collaborative representation,this paper proposes a face recognitional algorithm based on Gist feature and probabil istic collaborative representation (ProCRC).Firstly, it extracts the Gist feature of each face image,and projects them to optimal d iscriminant subspace by using the linear discriminant analysis LDA method,which can ensure that the LDA feature has the smallest cla ss scatter and maximum between class scatter. Then,it obtains the new learning dictionary by iteratively training the LDA fea ture using the LC-KSVD method,and the sparse coefficient is obtained by the ProCRC method.At last,it classifies them by calculating the probability that t he test sample belongs to each category. Experimental results on the ORL and extended YaleB database show that the face r ecognition rate can be significantly improved compared with the traditio nal collaborative representation.