Since channel state information (CSI) data can be utilized to sense the subtle changes in the environment, such as chest movement, we provide the analysis of CSI amplitude and phase as a basis for estimating breathing rates. In this paper, a breathing rate monitoring system is proposed, in which CSI data is collected with Intel Wi-Fi Link 5300 wireless network interface card (NIC) and Linux 802.11n CSI Tool . To this end, an antenna and subcarrier selection method is proposed to select those CSIs which are sensitive to respiratory thoracic changes. Furthermore, multiple signal classification (MUSIC) is applied as our research method in the estimation of breathing rates. Extensive experiments are conducted to validate the effectiveness of the proposed system. Our experimental results demonstrate that the proposed system can not only effectively distinguish the breathing state differences of fast, slow, and apnea but also achieve a certain accuracy in the calculation of the breathing rates.