Classification models are very versatile, and is one of the fields that has given rise to the trend of machine learning. In a proper application of these algorithms I use information collected from a representative sample of US postcodes, then feed a classification model using Bayesian inference to predict the volume of people that have a characteristic, then apply that model to other unreached postcodes, in this way it is possible to apply geomarketing with a substantially more effectiveness than traditional methods.