This paper describes a method of age-group classification of young males based on their facial images. The facial shapes of males and females are mostly formed by age 20 and 15, respectively. Our study only considered young males as they have a longer period during which facial shape is a determining factor in age estimation. Age classification was carried out using artificial neural networks. We employed 440 facial images in our experiment, composed of 4 different photographic images taken at ages 12, 15, 18 and 22 of 110 young males. Two methods of age classification were used, each employing different features extracted from the facial images, namely, "mosaic features" and "KL features. " As a result, we obtained about an 80% successful classification rate using mosaic features, and a slightly lower rate using KL features. We also analyzed the connection weights between the hidden and input layers of the trained networks, and examined facial features characteristic to each age group.