Small UAV applications are spreading rapidly in the commercial and defense sectors. However, their post-stall performance is lacking compared to their biological counterpart. Birds can outperform small-scale UAVs, especially during high angle of attack maneuvers, such as landing, takeoff, hovering, and perching. Prior research studied the effects of some aerodynamic devices that birds use, such as covert feathers and alula, on post-stall lift enhancements. Nevertheless, all the studies so far arrive at descriptive conclusions rather than a mathematical expression that can adequately describe the system. This paper uses the design of experiments augmented with linear regression and analysis of variance techniques to derive empirical models that relate the pre-and post-stall changes in lift and drag to two bioinspired flow control devices' deployment parameters, namely a covert-inspired flap and an alula-inspired leading edge device. Results show that the DoE approach selected can capture the same trends published in the literature using one factor at a time (OFAT) experiments. Compared to the cost and time required to complete OFAT investigations, the DoE results in the paper are cheaper, equally accurate, and present quantitative models that can be used to design and control these flow control devices during complex flight conditions.