Abstract: In order to rapidly estimate out hyaluronic acid content in fermentation broth,the relativities and partial correlation analysis between hyaluronic acid content with biomass,turbidity,conductivity,viscosity,reducing sugar were analyzed. The most significant indicators related to the content of hyaluronic acid were selected to construct the mathematical models of linear fitting,quadratic curve regression,BP neural network,and the models were verified to estimate the content of hyaluronic acid in fermentation broth. The results showed that at 0.01 level of significance,there was little relativity between turbidity,conductivity in fermentation broth and hyaluronic acid content;biomass had a false correlation with hyaluronic acid content;yet the relationships between hyaluronic acid content and viscosity,reducing sugar in fermentation broth was perfectly association,the correlation coefficients were 0.984,-0.869 respectively. The results showed that viscosity was the most significantly correlated with hyaluronic acid content,viscosity in fermentation broth could be considered as the optimized characteristic indicators to estimate hyaluronic acid content and structuct mathematic models. Three mathematic models were tested by estimation experiment of the hyaluronic acid content in fermentation broth showed that the estimation by BP neural network was the best and the variance was only 1.89×10^-2. The content of hyaluronic acid could be quickly and accurately estimated by measuring the viscosity of fermentation broth.