With the development of synthetic aperture radar (SAR) technology, the amount of data acquired by SAR increases rapidly. When SAR images are used to identify targets, the amount of calculation is large and time-consuming. In order to realize fast and effective recognition of targets, we propose a fast classification method of targets based on geometric model. In this method, binary target region and shadow region are selected as features. First, the forward features are predicted by using the optical visible information of the target geometry model. Then, the binary region extracted from the measured SAR images is aligned with the predicted binary region to establish the correlation. Finally, by judging the similarity criterion, the target classification is realized, and the efficiency and validity of the method are verified on MSTAR data set. Since this method does not involve time-consuming electromagnetic calculation, it can reduce the amount of calculation and accelerate the speed of target recognition.