The traditional spectrum algorithms are limited in face recognition problem. For its characteristics of problem, a novel method based on multireproducing Kernel Hilbert space was proposed. Firstly, the images were processed by the landmark method, and the angle of training images could be obtained. Secondly, the face data was iterated by the Kernel, then face data expressed linearly in the reproducing Kernel Hilbert space. Thereafter, for many types of face data, the multireproducing Kernel Hilbert space were established. Finally, the reproducing Kernel Hilbert space belonging of human face image was judged by the comparison of training images, and the multiangle face recognition achieved. The two classes of data sets were selected as the experimental data, which consisted of FERET and CMUPIE. A large number of experiments were carried out. The results show that the proposed method has great effect to recognise multiangle face. The average recognition rate and efficiency are 5% and 20% higher than the traditional algorithms, respectively.