Based on daily gas load and meteorological observation data during heating period in Xi’an of Shaanxi Province from 15 November 2009 to 14 March 2019, the variation characteristics of gas load in heating period, holidays and weekends were analyzed. The significant influence factors on gas load were selected by using correlation analysis. And on this basis the daily forecast model of gas load in heating period was established by using multiple linear regression method, then the forecast model was tested. The results show that the natural gas consumption during heating period gradually increased in Xi’an in past 10 years, the daily gas load presented a single-peak pattern change, and the peak appeared in January. The weekend and holidays effects of gas load were obvious during heating period, the gas consumption on weekend and holiday was less than that on working days, and the longer holiday was, the less gas load was. The gas load was significantly and positively correlated with gas load on previous day, while that was significantly and negatively correlated with meteorological factors of the maximum and minimum temperature, mean temperature and human body comfortable degree, and the correlation between heating gas load separated from actual gas load and meteorological factors obviously improved. Based on the above five influence factors, the dynamic forecast model of daily heating gas load was established by using multiple linear regression method. Upon inspection, the average relative error of the model was 3.4%, and the model was more stable in rush hours of using gas, the average relative error was 2.77%, which could meet gas dispatch needs of natural gas companies.