The goal of this project is to use inspiration acquired from bird flight to optimize the wing planform of micro-air vehicle wings. Micro-air vehicles are used by the military for surveillance and for search and rescue missions by civilian first-responders. These vehicles fly in the same low Reynolds number regime as birds, and have low aspect ratios similar to the pheasants and grouse of the order Galliformes. Conventional analysis is difficult for low Reynolds numbers, prompting use of biologically inspired methods of optimization. Genetic algorithms, which mimic the process of evolution in nature, were used to define wing shapes that were tested in wind tunnel experiments. In these experiments, lift-drag ratios at various angles of attack were measured on scale model micro-air vehicle wings (with variable length feathers) similar in shape to a bird wing. The planform shape of the scale model wing evolved in the wind tunnel flow over successive generations to ultimately produce superior wings with higher lift-drag ratios. The low angle of attack wings were easily optimized into a wing shape different from and potentially more efficient than the oft-used Zimmerman planform. The process was repeated for a higher angle of attack, near stall conditions, which yielded a different wing planform shape. Chord distributions of the optimized low angle of attack wings were found to closely match the same distributions of birds from the order Galliformes. Results from flow visualization studies meant to illuminate possible physics responsible for the higher lift-drag ratios were also investigated.