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Abstract. Biomass is an essential parameter for plant phenotyping, which can be used to assess plant vigor and root growth. This research aimed to develop a model to estimate maize biomass rapidly. Maize was sampled and weighted at the V8 growth stage during 2015 and 2016. Maize height, stem long diameter, and stem short diameter were used as input parameters. Multiple regression methods were carried out to develop the biomass models. Fresh weight and dry weight of maize in 2015 were used to build the biomass model, which was used to estimate maize biomass in 2015. The coefficient of determination between the true values and predicted values is high, and root mean square error, relative root mean square error are low. After that, the biomass models were also used to predict maize biomass in 2016. The result shows that the models have a good performance, for the best model: the coefficient of determination for maize fresh weight and dry weight is 0.890, 0.887, root mean square error is 17.056g, 1.417g, and relative root mean square error is 18.49%, 10.17%, respectively, indicating that the model can be used to estimate seeding maize biomass for the following season.