A major challenge in maize breeding programs is the selection of the best combinations of inbreds lines, which is essential for the development of high-yielding maize hybrids. This can become difficult in distinct environments as high plant population densities since the plant population can influence the combining ability among lines. Thus, our objective was to estimate the combining ability among maize inbred lines under traditional and high plant populations. Trials consisted of 121 single-cross hybrids derived from two sets of lines using a factorial-mating design. Hybrids were field-grown side-by-side at traditional (60,000 plants ha-1) and high (90,000 plants ha-1) plant population at an experimental station located in Coimbra, Minas Gerais. Each trial was implemented in an alpha-lattice design with two replications. Five traits were evaluated: days to silking (DTS) and pollen shedding (DPS), plant (PH, cm) and ear height (EH, cm), and grain yield (GY, kg ha-1). Estimates of the effects of general (GCA) and specific combining ability (SCA) were performed using a mixed model approach for each experiment. Spearman’s correlation was calculated for GCA effects of inbred lines between trials. The GCA variance component was statistically significant (P<0.05) for all traits in both arrays of lines (Groups 1 and 2) and plant population experiments. The SCA source of variation was also significant for the set of traits and individual environments. The selection accuracy estimates ranged from 0.83 (GY) to 0.96 (PH), and from 0.87 (GY) to 0.95 (EH), under traditional and high plant densities, respectively. Spearman rank correlation coefficients for GCA estimates were strongly significant and positive for all traits between experiments. For GY in Group 1, the inbred lines VML154 and VML035 emerged as the highest GCA at both plant populations. In Group 2, VML118 and VML029 were the best ones. We conclude that there is a strong association among the best inbred lines with desirable GCA effects for promising hybrids under traditional and high plant populations.