The study of entrainment of environmental air into developing cumulus clouds has many applications, ranging from the parameterizations of entrainment used by forecast models to the impact that entrainment has on large scale dynamics. However, it is difficult to measure the entrainment rate directly. A method to remotely retrieve cumulus entrainment from lidar measurements collocated with other remote sensing instruments will be presented. A cloud parcel model serves a forward model of an iterative retrieval algorithm. Water vapor mixing ratio observations from the Atmospheric Radiation Measurement (ARM) Raman lidar are ingested by the cloud parcel model along with temperature profile retrievals from the Atmospheric Emitted Radiance Interferometer (AERI) and vertical velocity observations from a cloud radar. The entrainment rate in the model is iteratively adjusted until the modeled effective radius and liquid water path match observations retrieved by the MIXCRA algorithm on AERI data within a specified tolerance. Preliminary results will be shown.