In this paper we present a new, data-driven mapping of five ACT-R modules on the brain. In the last decade, many studies have been published that evaluated ACT-R models based on their ability to predict fMRI data in certain predefined brain regions. However, these predefined regions were based on a reading of the literature, and might not be optimal. Currently, we used the results of a model-based fMRI analysis of five datasets to define a new brain mapping for the problem state, declarative memory, manual, visual, and aural modules. Both the original and the new mapping were applied to data of an experiment that elicited differential activity in these five modules; the results were compared to model predictions. The new mapping performed slightly better for the problem state, declarative memory, aural, and manual modules, but not for the visual module. In addition, it provides a more principled way of validating ACT-R models. Although the mapping is ACT-R specific, the methodology can be use to map any cognitive architecture or model to the brain.