T Objective: In pediatric clinical trials and cohort stuies, actual height, weight and head circumference of children at aspecific age may be required for certain developmental assessmentssuch as energy expenditure. This necessitates the choice of agrowth model with desired characteristics to predict heightweight accurately. Material and Methods:we compared Logistic and Gompertz models, which aremost commonly used growth curve modelsliterature, using different parameterization and in a race and genderspecific fashion on actual participant data from the CANDLE study,which is a prospective birth cohort of motherCounty, Tennessee, USA. We compared these competitive modelsand different parameterizations in terms of the size of theas well as prediction standard error, for each anthropometric meaurement, namely, height, weight, and head circumference. We alsoassessed the impact of missing data on these models.have shown that Gompertz model with the first orrameter defined with a subject-specific random effect is the bestmodel in terms of prediction accuracy. Although the sameGompertz model fitted on each individual profile without a randomeffect also has similar prediction accuracy, it has inerror of estimation as expected, thus, not recommended to be used.Conclusion: We conclude that Gompertz model with only the firstor the second parameter defined with a random effect performs thebest with and without missing data for heigcircumference growth in the first four years of life.