In this paper, we present a novel approach to age recognition from facial images. The method we propose, combines several established features in order to characterize facial characteristics and aging patterns. Since we explicitly consider age recognition in the wild, i.e. vast amounts of unconstrained Internet images, the methods we employ are tailored towards speed and efficiency. For evaluation, we test different classifiers on common benchmark data and a new data set of unconstrained images harvested from the Internet. Extensive experimental evaluation shows state of the art performance on the benchmarks, very high accuracy for the novel data set, and superior runtime performance; to our knowledge, this is the first time that automatic age recognition is carried out on a large Internet data set.