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Machine learning tools have been increasingly applied to structural brain magnetic resonance imaging (MRI) scans, largely for developing models to predict clinical phenotypes at the individual level. Despite significant methodological developments and novel application domains, there has been little effort to conduct benchmark studies with standardized datasets, which researchers can use to validate new tools, and more importantly conduct an objective comparison with state-of-the-art algorithms. The MICCAI 2014 Machine Learning Challenge (MLC) will take a significant step in this direction, where we will employ four separate, carefully compiled, and curated large-scale (each N > 70) structural brain MRI datasets with accompanying clinically relevant phenotypes. Our goal is to provide a snapshot of the current state of the art in the field of neuroimage-based prediction, and attract machine-learning practitioners to the MICCAI community and the field of medical image computing in general. We believe MICCAI 2014 MLC will be a perfect complement to the MICCAI 2014 main conference, the MICCAI 2014 Machine Learning in Medical Imaging Workshop and our sister challenge at MICCAI 2014 CADDementia, which is focused on diagnosing Alzheimer's disease from brain MR scans.