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Regionalization of maize cultivars cultivated with a relatively large scale always fails to take fully consideration of differences of performances among varies cultivars due to the limitation of data and method, and thus often provides inaccurate indications for maize cultivars deployment, which caused serious economic losses. To make a further effort to solve the problem, an effective regionalization method for maize cultivars cultivated in Huang-Huai-Hai Plain of China was proposed. The study was based on six years (2001—2006) of regional trial data, which covered 40 maize-testing locations and plantation survey data on field production, including the agronomic characters, various stresses and plantation management information, and the climatic data was used as well. Firstly, statistical analysis on trial data and survey data was applied to filter indexes which had a high frequency of occurrence, a significant impact on yield and a strong relationship with environments. As a result, the accumulated temperature higher than 10℃, average planting density, blank-stem stress, lodging stress and leaf blight stress were taken as indexes. Secondly, quantitative expressions of each index basing on their relationship with weather and management scheme in field production were established, and then the comprehensive index value was calculated and assigned to each county. Finally, counties were clustered by their comprehensive index value, and the spatial continuity adjustment was combined to achieve a spatially coherent clustering result. Consequently, maize variety Xiuqing 73-1 was taken as an example, and 606 counties of Huang-Huai-Hai Plain were classified into 5 regions, outlier counties of each region were identified and analyzed whose comprehensive index values were greater than the upper limit or less than the lower limit. The result can provide a practical guidance for precise cultivar popularization of maize.