Human age estimation in face images has become an active research topic in computer vision because of many potentially useful applications. However, the face may be unavailable or unusable in reality, especially for noncooperative users. So, a question is raised: Is it still possible to extract some relevant information on age when the face cannot be used? A new idea for age classification based on human body anthropometry is proposed which does not rely on the face. Based on this idea, a computational algorithm is developed to separate children from adults using relative lengths of body parts. To demonstrate the feasibility of this technique, the proposed age classification method is applied to two public databases of articulated human body images. A good accuracy is achieved on both databases, which is very encouraging.