Illuminating the primary sequence encryption of enhancers is central to understanding the regulatory architecture of genomes. We have developed a machine learning approach to decipher motif patterns of hindbrain enhancers and identify 40,000 sequences in the human genome that we predict display regulatory control that includes the hindbrain. Consistent with their roles in hindbrain patterning, MEIS1, NKX6-1, as well as HOX and POU family binding motifs contributed strongly to this enhancer model. Predicted hindbrain enhancers are overrepresented at genes expressed in hindbrain and associated with nervous system development, and primarily reside in the areas of open chromatin. In addition, 77 (0.2%) of these predictions are identified as hindbrain enhancers on the VISTA Enhancer Browser, and 26,000 (60%) overlap enhancer marks (H3K4me1 or H3K27ac). To validate these putative hindbrain enhancers, we selected 55 elements distributed throughout our predictions and six low scoring controls for evaluation in a zebrafish transgenic assay. When assayed in mosaic transgenic embryos, 51/55 elements directed expression in the central nervous system. Furthermore, 30/34 (88%) predicted enhancers analyzed in stable zebrafish transgenic lines directed expression in the larval zebrafish hindbrain. Subsequent analysis of sequence fragments selected based upon motif clustering further confirmed the critical role of the motifs contributing to the classifier. Our results demonstrate the existence of a primary sequence code characteristic to hindbrain enhancers. This code can be accurately extracted using machine-learning approaches and applied successfully for de novo identification of hindbrain enhancers. This study represents a critical step toward the dissection of regulatory control in specific neuronal subtypes.[Supplemental material is available for this article.]In metazoans, precise spatiotemporal patterns of gene expression are modulated by the exquisite contributions of transcriptional regulatory sequences. These include enhancers that activate transcription in a manner frequently observed to be independent of distance, position, and orientation with respect to the promoter of their target genes (Banerji et al. 1981). Empirically validated enhancers are typically a few hundred base pairs long and comprise binding sites for multiple transcription factors (TFs). In turn, TFs bound to these sequences also interact with common co-activators, communicating with the basal transcription machinery assembled at the promoter, and increasing the rate of transcription (Bulger and Groudine 2011). Identifying the combinatorial protein-DNA and protein-protein interactions that determine spatial and temporal enhancer function is crucial to understanding how distinct cellular and developmental programs are established.The systematic discovery of enhancers has proven challenging, since they are often located at great genomic distances from the genes they regulate (Lettice et al. 2003). The classical approach to enhancer identification invo...