The purpose of the study was (a) to assess the accuracy of the regression equations available in the literature to estimate the actual peak power (PPac) of the countermovement jump (CMJ) executed by young male soccer players, (b) to develop new regression equations from this population, and (c) to verify whether regression equations obtained from age-based subgroups could increase the accuracy of the estimation (PPes) of PPac. In all, 117 young players (age: 13.6 ± 2.4 years) were enrolled in the study. Each subject performed 5 CMJs on a force platform. The new regression equations were obtained from the entire experimental sample (G1) and 3 age-based subsamples (G2 = prepubertal, G3 = peripubertal, G4 = postpubertal) using 2 different approaches: the best jump and the mean values achieved by each subject. All the equations in the literature underestimated the peak power (p < 0.00005) in all the groups. The approach based on the mean values was more accurate (adjusted R = 0.925, SEE = 302.9 W) than the one based on the best jump (adjusted R = 0.892; SEE = 360.8 W). Moreover, calculating the regression equations from the 3 age-based subsamples, SEE resulted improved (15.5% in G2, 5.6% in G3 and 0.9% in G4). Regression equations must be derived from homogeneous populations, in terms of gender, sports practice, and age. The approach based on the mean values for each subject was more accurate than the approach used in the literature up to now. In practical applications, regression equation estimates cannot be used to assess the performance of a single subject, because errors may exceed 50%, whereas they may be useful for group comparisons.