The common methodology for the genetic evaluation of the egg production in poultry is to use cumulative data. However, the source and the scale of variation in egg laying are not constant during the whole period and thus, longitudinal models might offer more accurate predictions. Random Regression Models (RRMs) allow for differences in the phenotypic trajectory within a population and for these to be decomposed for each individual into genetic and environmental components. A similar approach is widely used in dairy cattle, where RRMs have underpinned the development of test day models for genetic evaluation. The objective of this study was to investigate the application of RRMs in the egg production of turkeys.