We present a system that generates original music designed to match a target emotion. It creates n-gram models, Hidden Markov Models, and other statistical distributions based on musical selections from a corpus representing a given emotion and uses these models to probabilistically generate new musical selections with similar emotional content. This system produces unique and often remarkably musical selections that tend to match a target emotion, performing this task at a level that approaches human competency for the same task.