It has been promising to provide personalized services for improving our living environment in support of information technologies. Sitting is one of the natural actions in our daily life. We focus on sitting behavior as a cue for providing such services. We used a pressure sensor seat on a chair for identifying sitting postures. In the experiments, we classified nine postures, including leaning forward / backward / right / left and legs crossed. We obtained classification rates of 98.9% when the sitting person was known and 93.9% when the person was not known.