Diagnosis of psychiatric disorders is based primarily on subjective symptoms, and neuroimaging or other biological examinations are used for excluding organic disorders. Advances in artificial intelligence technologies, such as machine learning, may enable us to utilize neuroimaging for individual diagnosis of psychiatric disorder or treatment response prediction. In addition, such technologies may elucidate the underlying pathophysiology of psychiatric disorders. In this article, we review studies that utilized machine learning on structural magnetic resonance imaging for depression.