Incorporating genotype-by-environment (GE) interaction effects into genomic prediction (GP) models with multi-environment climate data can improve selection accuracy to accelerate crop breeding but has received little research attention. Here, we conducted a cross-region GP study of grain moisture content (GMC) and grain yield (GY) in maize hybrids in two major Chinese growing regions using data for 19 climatic factors across 34 environments in 2020 and 2021. Predictions were conducted in 2,126 hybrids generated from 475 maize inbred lines, using 9,355 single nucleotide polymorphism markers for genotyping. Models based on genomic best linear unbiased prediction (GBLUP) incorporating GE interaction effects of 19 climatic factors associated with day length, transpiration, temperature, and radiation (GBLUP-GE