One of the major parameters in music is the overall speed of a musical performance. In this study, a computational model of speed in music audio has been developed using a custom set of rhythmic features. Speed is often associated with tempo, but as shown in this study, factors such as note density (onsets per second) and spectral flux are important as well. The original audio was first separated into a harmonic part and a percussive part and the features were extracted separately from the different layers. In previous studies, listeners had rated the speed of 136 songs, and the ratings were used in a regression to evaluate the validity of the model as well as to find appropriate features. The final models, consisting of 5 or 8 features, were able to explain about 90% of the variation in the training set, with little or no degradation for the test set.