Localization of mobile wireless devices carries critical importance for applications such as search and rescue, public safety, surveillance, and occupancy monitoring. In this paper, we study the problem of localizing WiFi-enabled mobile devices such as smartphones and tablets using the measurements captured by an unmanned aerial vehicle (UAV). We make use of the continuously broadcasted WiFi probe requests from mobile devices, capture them at different locations at a WiFi sniffer carried by a UAV, and subsequently estimate the user's location using random-forest based machine learning technique. More specifically, the geographical area of interest is partitioned into multiple zones, and based on the measured probe requests, we are interested to identify the zone where the WiFi device is located. Our experimental results show that the WiFi device can be detected in correct occupancy zone with a 81.8% accuracy.