Abstract: Chilling damage is one of the most destructive disasters for spring maize in Northeast China (Heilongjiang Province, Jilin Province, and Liaoning Province). Proper indicators of spring maize chilling damage are important for understanding the spatio-temporal distribution characteristics of disaster, dynamic monitoring, early warning, and conducting risk assessment. Therefore, it is of great scientific significance for the safe production and reasonable spatial planting of spring maize in China. Daily time series of air temperature during the past 55 years (1961-2015) at 82 meteorological stations, phenology at different developmental stages of spring maize from 1981 to 2013 at 61 agro-meteorological stations, and historical chilling damage records during the past 55 years (1961-2015) are jointly used to establish chilling damage indicators of spring maize at different developmental stages. The heat index with significant biological basis is selected as a factor, and its average at different developmental stages of spring maize is calculated based on three physiological temperatures. And then, 15 heat index sets of spring maize chilling damage samples collected from historical disaster records are built in the context of the combinations of five developmental stages of spring maize (seedling to clover, clover to jointing, jointing to blossom, blossom to milk, milk to physiological maturity) and three chilling damage levels (light, moderate, and severe). Kolmogorov-Smirnov (K-S) test method is used in checking the best distribution fitting functions of the heat index sets, and 15 normal distribution functions are established by comparing three fitting functions, including normal distribution, exponent distribution, and evenly distribution. Each critical threshold of spring maize chilling damage levels at different developmental stages is determined by using the upper limit of 95% confidence interval. The rationality of the spring maize chilling damage indicator is validated by using 25 independent samples. Results show that the verification based on the spring maize chilling damage level indicators is detected to be basically consistent with historical records, with 80% assessment being thoroughly consistent and all the errors of validation samples being within one level. Meanwhile, consistent rates of chilling damage indicators for three chilling damage levels are all above 75%.