We investigate the problem of reading level assessment for German texts on a newly compiled corpus of freely available easy and difficult articles, targeted at adult and child readers respectively. We adapt a wide range of syntactic, lexical and language model features from previous research on English and combined them with new features that make use of the rich morphology of German. We show that readability classification for German based on these features is highly successful, reaching 89.7% accuracy, with the new morphological features making an important contribution.