High levels of gait asymmetry are associated with many pathologies. Our long-term goal is to improve gait symmetry through real-time biofeedback of a symmetry index. Symmetry is often reported as a single metric or a collective signature of multiple discrete measures. While this is useful for assessment, incorporating multiple feedback metrics presents too much information for most subjects to use as visual feedback for gait retraining. The aim of this article was to develop a global gait asymmetry (GGA) score that could be used as a biofeedback metric for gait retraining and to test the effectiveness of the GGA for classifying artificially-induced asymmetry. Eighteen participants (11 males; age 26.9 y [SD = 7.7]; height 1.8 m [SD = 0.1]; body mass 72.7 kg [SD = 8.9]) walked on a treadmill in 3 symmetry conditions, induced by wearing custom-made sandals: a symmetric condition (identical sandals) and 2 asymmetric conditions (different sandals). The GGA score was calculated, based on several joint angles, and compared between conditions. Significant differences were found among all conditions (P < .001), meaning that the GGA score is sensitive to different levels of asymmetry, and may be useful for rehabilitation and assessment.