Objective: To construct an early warning model of fall risk for the elderly based on six kinds gait parameters. Method: A digital field was used to collect six kinds gait parameters for the elderly with a history of falls and no history of falls, binomial logistic regression analysis was used to establish a regression equation for predicting the risk of falls in the elderly, and an early warning model was constructed. Results: (1) The regression equations constructed according to the six kinds gait parameters are statistically significant. The overall correct rate is predicted from high to low: closed eyes walk forward(97.1%), open eyes walk backward (92.9%), closed eyes walk backward (88.6%), open eyes walk forward(87.1%), open eyes up and down (85.7%), open eyes turn left and right (82.9%).(2) The constructed early warning model for fall risk of the elderly mainly includes five steps of judgment, test, extraction, calculation and early warning, which is suitable for gait testing and evaluation of the elderly in the laboratory. Conclusions: (1) Six kinds gait parameters can predict the fall risk of the elderly. The best predictive effect of closed eyes walk forward is the best gait to predict the fall risk of the elderly. (2) The established early warning model of fall risk for the elderly is used to predict the fall risk within the age of 65-75 years old, and can provide early warning based on the probability of falling, which has a positive effect on preventing falls in the elderly.