This paper presents a statistical modeling approach of the real-life user-induced randomness due to mobile phone orientations for different phone usage types. As well-known, the radiated performance of a wireless device depends on its orientation and position relative to the user. Therefore, realistic handset usage models will lead to more accurate over-the-air characterization measurements for antennas and wireless devices in general. We introduce a phone usage classification based on the network access modes, e.g., voice (circuit switched) or non-voice (packet switched) services, and the use of accessories, such as wired or Bluetooth handsets, or a speaker-phone during the network access session. The random phone orientation is then modeled by the spherical von Mises-Fisher distribution for each of the identified phone usage types. A finite mixture model based on the individual probability distribution functions and heuristic weights is also presented. The models are based on data collected from built-in accelerometer measurements. Our approach offers a straightforward modeling of the user-induced random orientation for different phone usage types. The models can be used in the design of better handsets and antenna systems as well as for the design and optimization of wireless networks.