We investigate the relationship between air quality index and maternal health outcome markers including infant birthweight and maternal eclampsia. The air quality data are from the EPA Outdoor Air Quality monitors, and maternal health data are Vital Statistics Natality Birth Data from the National Center for Health Statistics. We train classification models (Ridge and SVM) on natality data both with and without air quality index data to predict instances of maternal eclampsia and low infant birth weight. The models are evaluated using training and testing accuracies and rates of false negatives, which we aim to minimize. A highly accurate prediction model of this type can provide useful information to pregnant individuals about their risk level for eclampsia or infant low birth weight based on geographic, demographic, and health risk factors.