Recent work has shown that average vehicle flow and density on urban traffic networks are related and can be used to describe traffic conditions across a network. This relationship, known as the Macroscopic Fundamental Diagram (MFD), can also be used to describe network dynamics, unveil insights into network behavior and develop network-wide control strategies to improve efficiency. However, deriving the MFD of a network is difficult due to large data requirements. In this work, we propose a method to estimate average network flows and densities using trajectory data from mobile vehicle probes that is becoming increasingly available through advances in Intelligent Transportation System technologies and the Connected Vehicle program. This information can be used to directly estimate the MFD, and could also be used to monitor traffic conditions in real time if the requisite probe data is available. This methodology is tested on a micro-simulation network and shown to be very accurate when mobile probe penetration rates reach at least 15%. The only drawback is a requirement that this penetration rate is known a priori. However, if this probe data is obtained through the Connected Vehicle program, it is likely that the penetration rate would be known and slow changing with time. If other sources are used, the penetration rate can also be estimated in real time using additional data from traditional traffic sensors.