Gait analysis has received significant attention in many clinical conditions including chemotherapy-induced alterations, degenerative diseases, and hemophilia. Gait changes can be a consequence of physical and/or neural/motor alterations and/or pain. It can provide measurable objective outcomes for following disease progression and the effectiveness of therapy without patient or observer bias. Many devices are available for analyzing gait in clinic. Gait analysis in laboratory mice is frequently used to examine the mechanisms and effectiveness of interventions for movement and pain assessment. However, gait analysis in mice is challenging due to the complexity of image acquisition and analysis of large data sets. We have developed a relatively simple method to analyze gait and validated it using the arthropathy model in hemophilia A mice. We describe artificial intelligence-assisted detection of gait and validation with weight-bearing incapacitance for stance stability in mice. These approaches enable the non-invasive, non-evoked evaluation of pain and the consequent impact of motor function on gait.