Abstract: An evaluation index of spring maize waterlogging was constructed to analyze the spatial and temporal distribution characteristics in Northeast China. Daily meteorological, maize growth period, and historical disaster data were collected from 164 meteorological stations from 1981 to 2020. Pearson correlation analysis was used to screen the key disaster-causing factors of spring maize sowing-emergence seedling waterlogging. An analysis was made on the effects of early precipitation and temperature on the level of waterlogging. The stepwise regression was utilized to construct the equivalent precipitation and equivalent temperature, particularly with the degree of waterlogging as the dependent variable, while the factors with a significant impact on the waterlogging as the independent variables. A normality test of equivalent precipitation and the equivalent temperature was carried out to construct the waterlogging grade index. The lower confidence limit of 95% confidence interval was taken as the index critical value of mild, moderate and severe waterlogging grade of spring maize. The occurrence of waterlogging in the sowing-emergence stage of maize was inverted to analyze the availability of the index, compared with the historical disaster data of waterlogging. The trend analysis and mutation test were performed on the M-K test at the maize sowing-emergence stage waterlogging from 1981 to 2020. The spatial distribution and interdecadal variation characteristics were obtained for the different degrees of waterlogging. The results show: 1) The precipitation in the current process of waterlogging and the cumulative precipitation from 1 to 10 days before the process were significantly positively correlated with the grade of waterlogging disaster. The average temperature in the current process of waterlogging and the average temperature from 1 to 5 days before waterlogging were significantly negatively correlated with the grade of waterlogging disaster. Therefore, the waterlogging index was constructed for the maize sowing-emergence stage. The basically consistent rate of index verification was 82%, indicating the excellent accuracy of the index. Consequently, a better representative was achieved in the actual disaster situation of maize waterlogging in this period. 2) There were outstanding spatial differences in the occurrence of waterlogging at the sowing-emergence stage of maize. Specifically, the main frequency was concentrated in the eastern region, whereas, there was a low frequency of waterlogging in the East Four Leagues. Among them, the highest frequency of waterlogging was distributed in the eastern part of Liaoning Province, the southeastern part of Jilin Province, and the Sanjiang Plain of Heilongjiang Province, with the highest frequency of waterlogging up to 45%. The range of mild waterlogging showed an expanding trend. But, there was no change in the range of other degrees of waterlogging. Great differences were found in the frequency of different degrees of waterlogging in maize. The frequency from the high to the low was mild > moderate > severe. 3) The frequency of maize waterlogging damage showed an overall upward trend, but the upward trend was not significant (not through the 0.05 significance test). Among them, the years 2001, 2002, and 2004 were the significant mutation years (through the 0.01 significance test). The finding can provide a theoretical basis to reveal the disaster mechanism and temporal and spatial evolution of spring maize waterlogging in Northeast China under the background of climate change. A reliable scheme can be achieved in the real-time monitoring of waterlogging.