Abstract: To address the issue of low prediction accuracy in wellbore liquid accumulation, it is crucial to enhance the precision of predicting the critical liquid loading rate in gas wells.This study, based on the annular flow liquid film theory, conducted a force analysis of the gas-liquid two-phase flow in the wellbore and established a critical liquid-carrying flow rate prediction model that comprehensively considers the impact of fluid flow state and liquid film thickness on friction coefficients. The newly developed model was adjusted using actual production data, and the adjustment results were verified with field data from the gas field.The results show that the adjusted model achieved a 100% prediction accuracy for liquid accumulation, with the prediction critical value error reduced to 0.21, a 47.5% reduction in prediction error compared to existing models. Additionally, the new model exhibited the lowest average relative error and root mean square error, improving by 89.7% compared to the prediction effects of existing models. A comprehensive comparison indicates that the new model outperforms other models in terms of prediction accuracy.The method of adjusting the liquid accumulation model with production data compensates for the discrepancies between theoretical models and actual production, enhancing the prediction accuracy and applicability of the model and resolving the challenge of inaccurate prediction of liquid accumulation in natural gas wells.