Phenotypic plasticity (PP) is the ability of an organism to produce multiple phenotypes in response to environmental changes. In cultivated species, such as maize (Zea mays L.), the PP of plant architecture traits will play an important role in the adaptation of genotypes to unpredictable scenarios given by climate change, marginal areas, and seeding with variable plant density (D). We bring information to improve the understanding of the environmental modulation of PPs of plant architecture traits of maize, untangling their genetic bases, and testing the hypothesis of independent genetic control of the traits per se and their PPs. The PP of traits related to leaf area, spatial distribution of leaf area and stem architecture [(leaf area (LA), maximum leaf width (LW), maximum leaf length (LL), leaf orientation value (LOV), vertical leaf angle (VA), leaf length to the flagging point (LF), LE/LL relationship (LFLL), azimuthal leaf orientation (AZ), ear height (EH), plant eight (PH), EH/PH relatioship (EHPH) and stem diameter (SD)] were estimated using 160 RILs from the IBM B73 × Mo17 Syn4 population, cultivated under two contrasting D (5 and 10 pl m− 2) during two growing seasons that determined different environmental conditions. Data were phenotypically analyzed and quantitative traits loci (QTLs) were mapped. For leaf area and stem architecture related traits, high mean values of traits per se were related with high PPs values at low intraspecific competition while low mean values were observed at high intraspecific competition. The opposite response was found on leaf orientation related traits, with the exception of AZ. Forty-eight QTLs were detected for PP of plant architecture related traits on all chromosomes with exception of chromosome 7. There was no phenotypic correlation and no co-located QTLs for traits per se and their PPs. This independent genetic control for traits per se and their PPs would allow breeders to develop genotypes adapted to specific environments selecting for high or low PP in combination with high or low values for relevant agronomic traits.