In the modern world there are many network risks which share a common structure: an isolated risk is amplified because it is spread by the network. In essence, all of these types of spreading phenomenon can be modeled as a rumor spreading through a network, where the goal is to find the source of the rumor in order to control and prevent these network risks based on limited information about the network structure and the rumor infected nodes. In this thesis, we shall use the so-called Rumor Spread model which is simplified from an epidemic model called Susceptible-Infected-Recovered model to study the Rumor Center in a tree-shaped network. Several new results are obtained on the cases where the network is defined on a d-regular tree either infinite or finite.