Pregnant women are exposed to numerous environmental chemicals, but there is limited understanding of chemical mixture exposure profiles and predictors. In a prospective cohort of 389 pregnant women from Cincinnati, OH, we used biomarkers to estimate exposure to 41 phenols, phthalates, metals, organophosphate/pyrethroid/organochlorine pesticides, polychlorinated biphenyls, polybrominated diphenyl ethers, perfluoroalkyl substances, and environmental tobacco smoke. Using pairwise correlations, k-means clustering, and principal component analysis (PCA), we identified several profiles of chemical exposure. Chemicals within structurally, commercially, or industrially related chemical classes (e.g., phthalates) were moderate to strongly correlated compared to unrelated chemicals (e.g., pyrethroid pesticides and environmental tobacco smoke). Using k-means clustering and PCA, we identified 3 clusters of women ( N = 106, 158, and 125) and 6 PC scores, respectively, that characterized profiles of cumulative chemical exposure. The first two PC scores significantly varied by cluster, indicating that some of these profiles could be identified using both methods. Cluster membership and PCA scores were associated with race, marital status, consumption of fresh fruits and vegetables, and parity. Future work could use clusters and PCA scores to characterize environmental chemical mixture exposures in other cohorts of pregnant women and predict potential health effects of environmental chemical mixture exposure.