Abstract: The moisture content of grains after physiological maturity (MCAM) is the key determinant of the quality of mechanical grain harvesting (MGH), which can significantly improve the production efficiency of maize. Therefore, the aim of this study was to accurately estimate MCAM, analyze the main influencing factors, and determine the harvest time of maize, and select appropriate varieties for MGH. In 2017 and 2018, spring maize field experiments were carried out in Botou, Nandagang, and Yutian of Hebei Province; and Yuci of Shanxi Province. Seven common maize varieties and three densities of each variety were set up each year to monitor MCAM. Variety characteristics, management, meteorological data, and grain moisture content after physiological maturity were determined. A model based on the diffusion theory was used to simulate MCAM considering the atmospheric temperature and humidity. The area under the dry down curve (AUDDC) was used to select the varieties that performed well in the grain dry down. The results showed that the model based on diffusion theory could simulate MCAM well. The year, site, and variety had significant influence on the grain moisture content at physiological maturity (M₀) and the moisture diffusion rate (k), which were parameters of the model. However, the planting density had no significant effect on these two parameters. Stepwise linear regression analysis showed that ET₀, the maximum temperature, and irrigation amount at grain-filling stage had significant positive effects on M₀. The ET₀ during the 30 days after physiological maturity and the rainfall in the middle-late grain-filling stage had significant positive effects on k. In contrast, rainfall during the entire growth period had a significant negative effect on k. The number of husk layers had the greatest influence on M₀ (positive effect), and the number of leaves had the greatest influence on k (negative effect). Ten days after physiological maturity, the MCAM of spring maize in North China could be reduced to 28% in almost all circumstances and to 25% in half of the circumstances. The AUDDC during the 10 days after physiological maturity of each variety, was calculated using the model. Compared with the average AUDDC, it was found that 'Jingnongke 728' 'Zhang1453' 'Huanong 887' 'Guangde 5' and 'Jinkeyu 3306' displayed excellent dry down performance.