This study aimed to develop statistical models describing the learning of endotracheal intubation (ETI). We collected data from 100 subjects undergoing ETI training with intubatable medical models and manikins (airway trainers). Trainees initially viewed a video about ETI and an instructor demonstrated the technique. Subjects then made up to 17 supervised trials. Each trial was scored as a success or failure; this score was the primary outcome used in analyses. Random effects and population-averaged logit models, and a learning model intended to quantify the relative contributions of failed and successful trials to the learning process, were fitted to the data. The logit models provided evidence of differences in difficulty between different airway trainers and differences in success rate related to previous ETI experience. Trainees became familiar with an airway trainer after multiple trials, as demonstrated by a 50% decrease in the odds of successful ETI when starting on a new trainer. The learning model indicated that a trainee learns about as much from 1 successful ETI as from 12 (95% confidence interval, 2-23) failed trials. The results demonstrate the feasibility of statistical modeling of the learning of ETI and provide insight into the learning process.