This paper aims to adapt clusterwise regression to interval-valued data. The proposed approach combines the dynamic clustering algorithm with the center and range regression method for interval-valued data in order to identify both the partition of the data and the relevant regression models, one for each cluster. Experiments with a car interval-valued data set show the usefulness of ombining both approaches.