Starting with liver, limb and brain enhancers and genomic background regions from six mammals, the first step of the pipeline quantified each of these genomic regions by their 5-mer spectrum—the frequency of occurrence of all possible length five DNA sequence patterns. Using the spectra as features, we trained a spectrum kernel support vector machine (SVM) to distinguish enhancers from non-enhancers in each species and evaluated their performance with ten-fold cross validation. Then, we applied classifiers trained on one species to predict enhancer activity in all other species. Finally, we evaluated the performance of cross-species prediction compared to within species prediction and quantified the similarity of different species’ classifiers by the sharing of TF motifs among the most predictive 5-mers. Limb and brain enhancer data were only available for human, macaque, and mouse.