Cytochrome P450 (CYP) superfamily represents the major drug metabolizing enzymes responsible for metabolizing over 65% of therapeutic drugs, including those for pediatric use. CYP-ontogeny based physiologically-based pharmacokinetic (PBPK) models have emerged as useful tools to mechanistically extrapolate adult pharmacokinetic data to children. However, these models integrate physiological differences in pediatric population including age-dependent differences in the abundances of CYP enzymes. Conventionally, developmental changes in CYP enzymes have been reported using protein abundance and activity data from subcellular fractions such as microsomes, which is prone to high technical variability. Similarly, the available pediatric pharmacokinetic data suffer from the lack of specific CYP substrates, especially in younger children. In the present study, we utilized viable hepatocytes from 50 pediatric (age, day 1- 18 yr) and 8 adult human donors and carried out global proteomics-based quantification of all major hepatic CYP enzymes, including orphan enzymes that have not been studied previously. While CYPs 2B6, 3A5, 4A11, 4F3, and 4V2 did not show significant association with age, all other quantified isoforms either increased or decreased with age. CYPs 1A2, 2C8, 2C18, and 2C19 were absent or barely detected in the neonatal group, while CYP3A7 was the highest in this group. The >1-2 yr age-group showed the highest total abundance of all CYP enzymes. The age-dependent differences in CYP enzymes reported in this study can be used to develop ontogeny-based PBPK models, which in turn can help improve pediatric dose-prediction based on adult dosing, leading to safer drug pharmacology in children. Significance Statement We quantified age-dependent differences in the abundances of hepatic CYP enzymes using a large set of viable pediatric and adult hepatocytes using quantitative global proteomics. We report for the first time the ontogeny in the abundance of CYP enzymes in human hepatocytes, especially, orphan CYPs 20A1, 27A1, 51A1, 7B1, and 8B1 and the CYP4 subfamily of enzymes. Our study provides important data about CYP ontogeny that can be used for the better prediction of pediatric pharmacokinetics using physiologically-based pharmacokinetic modeling.