Summary One in every 10 babies is born prematurely in the US, and this contributes to high rates of long-term negative health consequences. An even higher rate of preterm births is expected in the near future due to maternal coronavirus disease 2019 (COVID-19) infection. While premature birth does not necessarily result in developmental neuropsychiatric disorders, it is associated with elevated rates of autism spectrum disorder (ASD)1-9, intellectual disability10, 11, attention-deficit/hyperactivity disorder (ADHD)2, 12, learning disabilities13, cerebral palsy13, and delays in cognitive, social, and motor development2, 4, 8, 10, 14-16. The developmental risks and uncertainty associated with premature birth may overwhelm caregivers with confusion, stress, and anxiety about the future. Moreover, the heterogeneity of cognitive, social, and motor developmental trajectories among preterm infants confounds the accurate, early detection of developmental issues and the early implementation of therapeutic interventions17-21. As some forms of early intervention improve the prognoses of infants with (or at high risk of) developmental neuropsychiatric disorders22-28, an objective, quantitative method of predicting (or improving the prediction of) the developmental trajectories of preterm infants is urgently needed. A number of research groups have attempted to use computational models to differentiate the cries of preterm and term infants29-32. However, computational models that can predict the heterogeneous cognitive, social, and motor developmental trajectories among preterm infants do not exist. Moreover, the neural basis of how preterm birth alters the cognitive, social, and motor developmental trajectories is poorly understood. Based on our preliminary data, which showed that the volume of the amygdala is selectively impacted by a gene variant that is linked to social deficits in mice, we hypothesize that preterm birth also alters the cognitive, social, and motor developmental trajectories from the neonatal to early adult periods via variable alterations of brain structures relevant to cognitive, social, and motor capacities. To test this hypothesis, we will leverage our expertise in computational feature selection, using variables of neonatal vocalization and volumes of various mouse brain regions that best account for variances in cognitive, social, and motor capacities. A positive outcome will provide much-needed predictive models to further explore the mechanistic bases of cognitive, social, and motor development in mouse models. This should enable investigators to further evaluate the mechanistic, structural bases for heterogeneous cognitive, social, and motor trajectories in preclinical models of environmental and genetic risk factors.