This chapter reviews the basics and recent researches of computer-aided diagnosis (CAD) systems for assisting neuroradiologists in the detection, monitoring and prediction of multiple sclerosis (MS) in magnetic resonance (MR) images. The CAD systems consist of image feature extraction based on image processing techniques and machine learning classifiers such as linear discriminant analysis, artificial neural networks, and support vector machines. We introduce useful examples of the CAD systems in the neuroradiology and conclude with possibilities in the future of the CAD systems for MS in MR images.