In this paper, we study the problem of landmark recognition and propose to leverage 3D visual phrases to improve the performance. A 3D visual phrase is a triangular facet on the surface of a reconstructed 3D landmark model. In contrast to existing 2D visual phrases which are mainly based on co-occurrence statistics in 2D image planes, such 3D visual phrases explicitly characterize the spatial structure of a 3D object (landmark), and are highly robust to projective transformations due to viewpoint changes. We present an effective solution to discover, describe, and detect 3D visual phrases. The experiments on 10 landmarks have achieved promising results, which demonstrate that our approach provides a good balance between precision and recall of landmark recognition while reducing the dependence on post-verification to reject false positives.