Abstract: The planning outline of Xiong'an New Area clearly states that the proportion of blue-green space in the Xiong'an New Area will be stable at 70% in the future. Baiyangdian Lake is the largest wetland and water body in the Xiong'an New Area. Understanding and predicting changes in this water body is of great significance to ensure the production of domestic water and ecological security of the Xiong'an New Area. In order to predict the lowest water level of Baiyangdian Lake from October to April of the next year, and to guide water resources management and disaster prevention and mitigation of the Xiong'an New Area, a historical data regression method and a machine learning method were used to analyze the water level variation in the Baiyangdian Lake with different regional precipitation. It was found that the lowest water level of Baiyangdian Lake from October to April was highly correlated with both the mean precipitation in the current rainy season and the water level in May of that year. Based on this result, a method was established to predict the lowest water level in Baiyangdian Lake from the current rainy season until the next rainy season by using the precipitation data in the current rainy season and the water level before the current rainy season. According to the precipitation and water level data in Baiyangdian Lake from 2001 to 2017, the prediction model for the lowest water level was established. Furthermore, gradient descent algorithm was adopted for machine learning and training. After model verification, the lowest water level prediction model was developed based on the average rainfall from July to August/July to September and the water level in May as the prediction factors. The model was verified using the collected data; the fit of the model was acceptable as the simulated and predicted result errors were both below 5%. According to the Baiyangdian Lake water level in May 2018 and the average precipitation data of July to August/July to September 2018, the lowest water level of Baiyangdian Lake from October 2018 to April 2019 would be between 8.52 m and 8.38 m, which was higher than the lowest ecological water level of Baiyangdian Lake. According to the latest minimum water level from October 2018 to February 20, 2019, the model predicted result errors were below 4%. Thus, our model can predict the lowest water level of Baiyangdian Lake 3-7 months in advance, which provides a significant scientific basis to improve the comprehensive management and the rational allocation of water resources in the Xiong'an New Area.