The aim of the study was to estimate the association between medical imaging utilization, and socioeconomic demographic and clinical factors among pediatric patients visiting the Emergency department (ED), allowing for the development of predictive models. Secondary data analysis was conducted to predict the use of medical imaging in pediatric patients visiting the ED. Multivariate logistic regression models were applied to structured, unstructured and combined data, incorporating natural language processing. Of the 27,665 visits included in the study, 8,394 (30.3%) obtained an imaging diagnosis. The c-statistic was 0.71 for any imaging use, 0.69 for X-ray, and 0.77 for CT, in the predictive model including only structured variables. Models including only unstructured information obtained c-statistics of 0.81, 0.82 and 0.85, respectively. When both structured variables and free text variables were included, the c-statistics reached 0.82 for any imaging use, 0.83 for X-ray, and 0.87 for CT. We present several predictive models for the use of medical imaging in pediatric patients visiting the ED. The inclusion of unstructured data provided significant improvement in accuracy.