Nowadays, Telecommunication services providers face many challenges. Due to the great and dynamic growth in data communication usage. Moreover, the telecommunication market is very competitive with dynamic changes in demands centered on customer satisfaction and attraction. Consequently, planning the infrastructures of Telecommunication Access Network (TAN) is one of the most important and challenging tasks facing telecommunication companies especially after the trend of using optical fiber cables. Moreover, there is an increasing need to analyze and manage telecommunication’s network data carefully, which helps in planning the TAN. This thesis presents a proposed Telecommunication Fuzzy Rules system to identify appropriate MSAN’s locations (Multi Services Access Node) centered on utilizing the benefits of GIS and fuzzy rule system. The proposed approach goes through a number of phases steps. Firstly, such proposed system utilizes GIS features to identify proper data set. Secondly, appropriate membership function for fuzzy variables are generated by utilizing an integrated hybrid model PSO-TE (Particle Swarm Optimization-Total Entropy) for choosing the best parameters of subsets. Thirdly, identifying the proper fuzzy classifications rules for the telecommunication MSANs locations based on a set of MSAN’s planning barriers using the capabilities of the Artificial Bee Colony (ABC), correlation function and confidence rate as a fitness function and the mamdani inference system. The proposed system proved the ability for generating Telecommunication Fuzzy Rules for choosing suitable MSAN’s locations. The total classification accuracy of the proposed system is around 97.8%, which is better than other compared classification algorithm