本文通过灰色预测模型，收集2002~2019年武汉市住宅商品房平均价格作为基础数据，构建了武汉市住宅商品房平均价格变化趋势预测模型，本文运用了GM(1,1)模型、GM(2,1)模型和邓聚龙参数估计模型对武汉市住宅商品房平均价格进行预测，通过对三种预测方式的检验指标和预测值与实际值的比较，发现直接利用Python求解参数的GM(1,1)模型最终的预测结果对现场的参考意义更大；最终运用GM(1,1)模型计算和预测2020~2030年武汉市住宅商品房平均价格走势，从预测的结果来看，武汉市商品房的价格在未来会保持上涨的趋势。 In this paper, the average price of residential commercial housing in Wuhan City from 2002~2019 was collected as the base data through a gray forecasting model, and a forecasting model of the trend of the average price change of residential commercial housing in Wuhan City was constructed. The GM(1,1) model, GM(2,1) model and Deng Jurong parameter estimation model are applied to forecast the average price of residential commodity houses in Wuhan City. By comparing the test indexes and the predicted and actual values of the three forecasting methods, it is found that the final forecasting results of the GM(1,1) model, which directly uses Python to solve the parameters, are more meaningful for realistic reference. The GM(1,1) model was finally applied to calculate and predict the average price trend of residential commercial housing in Wuhan from 2020 to 2030, and from the predicted results, the prices of commercial housing in Wuhan will maintain an upward trend in the future.