Abstract: Systems and methods are presented for scheduling appointments efficiently by generating predictive models using historical appointment data and using these models to predict in advance whether an appointment will be a no-show or a cancellation. The predictive models may be based on logistic regression methods, support vector machines, or neural networks. If the model predicts that an appointment in a particular time-slot will probably be a no-show/cancellation, a scheduling system may decide to double-book that time-slot in order to reduce scheduling inefficiency.