A model-based approach for matching language learners to texts of appropriate difficulty is described. Results are communicated to test takers via a targeted reading range expressed on the reporting scale of an automated text complexity measurement tool (ATCMT). Test takers can use this feedback to select reading materials that are well matched to their abilities, that is, materials that are expected to be challenging, yet not so challenging as to cause frustration or reduce motivation. An application to the problem of helping students prepare to take the "TOEFL iBT"® test is presented.