Young children with upper airway problems are at risk for hypoxia, respiratory insufficiency and long term morbidity. Computational models and quantitative analysis would reveal airway growth patterns and benefit clinical care. To capture expected growth patterns we propose a method to build a pediatric airway atlas as a function of age. The atlas is based on a simplified airway model in combination with kernel regression. We show experimental results on children with subglottic stenosis to demonstrate that our method is able to track and measure the stenosis in pediatric airways.