In software-defined networking (SDN), the decoupled architecture provides opportunities for efficiently measuring critical quality of service (QoS) parameters, such as delay. Existing approaches, to dynamically obtain delay, are based around calculating the transit time of a probe packet that travels through the data links. These approaches are not efficient as the probe packet injected into the data plane incurs considerable overhead. Additionally, a separate probe packet is required to measure the delay of each queue if more than one queue is present on the egress port of a switch. Thus, these approaches are not scalable. In this paper, we propose an efficient passive delay estimation method, queueing delay monitoring (qMon), to monitor queueing delay in SDN networks. qMon leverages the OpenFlow protocol to obtain queue statistics from switches at regular intervals, which are further employed to estimate the mean queueing delay for each interval. Thus, the proposed approach differs from the existing approaches as no packet is injected into the data plane to measure delay. The results show that for Poisson traffic and for bursty traffic with large ON intervals, round trip time (RTT) values estimated using qMon and ping utility demonstrate high correlation when the measured RTT value is considered as time-series data.