In different parts of the world, telecenters have been in use to make people get benefit from information and communication technologies (ICT). In those centers disadvantaged people can access internet and use electronic services offered in a broad range. And rural inhabitants are among these disadvantaged people. Telecenters are required in rural areas not only to make people utilize ICT but also to contribute rural development. Electronic services bring about many opportunities for citizens in both daily and professional life. With the use of them, it is possible to raise living standards and increase productivity. ICT has a special importance for rural areas as ICT-supported implementations help people in rural areas reach information, services and markets that are hardly accessible in traditional ways. Therefore, rural telecenters are established and electronic services meeting rural requirements are served through them. In general the biggest challenge for telecenters is their sustainability. In rural areas this problem gets even bigger as demand for such services are relatively lower because of the lack of awareness and motivation. Thus they need to be carefully designed to ensure their sustainability and efficient use. For sure, their sustainability mostly rests on the electronic services offered to rural inhabitants through these centers. However, to ensure efficient use of them and also to serve everyone in the area, their location, number and capacity gain utmost importance, too. Regarding the low demand and the difficulty to sustain telecenters in rural areas, the best approach is to establish those centers in only select hub settlements to be reached easily from the villages in close vicinity. In this study, optimization methods were used to determine the location of those rural telecenters. Three location optimization problems as set covering, p-center and p-median were defined and then solved. In the set covering problem the number of the centers was minimized given a maximum travel distance from origin to destination, in the p-center problem the maximum distance between the destination and the village served from there was minimized given the number of telecenters required and in the p-median problem total travel distance in the area was minimized again given the number of telecenters. While each of the three models aims to serve all the villages in the area, their results differ reflecting the priority of that approach.