License plate recognition has many applications in traffic systems. It is very difficult because images are usually noisy, broken or incomplete. In this paper, a novel robust approach for license plate recognition is proposed, which combines subspace projection with probabilistic neural network to improve the recognition rate. Probabilistic neural network is used as a classifier to identify low-dimension test samples which are obtained from actual license plate images by subspace projection. Experiment results show the effectiveness of the proposed method.