Exposure to pollutants transferred from mothers to their eggs can impact the vitality, survival, and health of offspring immediately and later in life. This is especially true for non-avian reptiles that have experienced global declines and have high sensitivity to pollutants during embryonic stages. However, non-avian reptiles are often overlooked in pollution-related risk assessment and conservation efforts. A comprehensive database was created by systematically extracting, homogenizing, and integrating published scientific data on organic pollutants jointly measured in reptile mothers and their eggs. The database was enriched with molecular physicochemical properties of the pollutants. An orthogonal regression model was then developed to link the pollutant concentrations in mother and eggs while explicitly considering the measurement uncertainty in both variables. Over four decades, 17 publications provided 19,955 datapoints shifting from legacy pollutants (dioxins, polychlorinated biphenyls, organochlorine pesticides) to emerging contaminants (polycyclic aromatic hydrocarbons, toxaphene, plasticizers, paraffins, per- and polyfluoroalkyl substances) although research on newer contaminants lags regulatory and societal demands. Challenges including taxonomic bias, heterogeneity in sampled tissues, and 73% of censored data complicate comparative analyses. However, significant opportunities were identified including the potential use of the turtle M. terrapin and snake E. chinensis as flagship species where a large amount of data is available across tissues (allowing investigation into physiological relations and the use of less-invasive tissues such as blood) and compounds (allowing insights into maternal transfer across the chemical universe). We applied the orthogonal model to explore these research opportunities, and were able to predict concentrations in M. terrapin eggs for pollutants with a range of molecular properties. We then tested the predictive ability of this model to extrapolate towards other freshwater and marine turtle species. The integrated dataset and predictive model presented quantitative insights into the magnitude of maternal transfer of organic pollutants in non-avian reptiles in an era where scientists and society need to achieve more with limited wildlife data.