This paper describes the AuToBI tool for automatic generation of hypothesized ToBI labels. While research on automatic prosodic annotation has been conducted for many years, AuToBI represents the first publicly available tool to automatically detect and classify the breaks and tones that make up the ToBI annotation standard. This paper describes the feature extraction routines as well as the classifiers used to detect and classify the prosodic events of the ToBI standard. Additionally, we report performance evaluating AuToBI models trained on the Boston Directions Corpus on the Columbia Games Corpus. By evaluating on distinct speakers domains and recording conditions, this evaluation represents an accurate representation of the performance of the system when applied to novel spoken material.