Though female reproductive toxicity has not been the primary endpoint of focus in previous risk assessments for hexavalent chromium [Cr(VI)], additional studies have been published since authoritative assessments. Herein, the objective is to: (1) build on previous assessments, including both newer studies of apical outcomes and mechanistic data, and (2) apply systematic review methods to contribute in developing best practices in systematic review. Evidence was identified using a modified search strategy from the USEPA-IRIS Cr(VI) protocol to identify studies specific to female reproductive effects, resulting in 21 potentially relevant studies in experimental animals (no human data were identified as relevant) characterizing apical outcomes. These studies were then divided into lines of evidence by endpoint (e.g., implantation loss, number of live pups). Critical appraisal, conducted on the experimental level, involves assessment of reporting quality, risk of bias (RoB), and sensitivity, results of which highlight the need for topic-specific refinements to differentiate elements of validity. An added metric in the reporting quality assessment specific to oral feeding studies was to consider the potential reduction of Cr(VI) to Cr(III) and its impact on exposure. The findings determine the need to systematically review the mechanistic data (and demonstrate a stepwise application of systematic review). Initial evaluations of the utility and feasibility of mechanistic data were also conducted based on assessment of high-throughput screening (HTS) data from the ToxCast/Tox21 screening programs. Cr(VI) was tested in 22 assays related to endocrine signaling and exhibited inconsistent results between assays. In order to integrate these data systematically, observed activity (e.g., receptor antagonism) require additional assessment, including critical appraisal and biological-pathway-based considerations (including dose) relative to the potential for adversity. This application highlights the advantages of applying systematic review techniques as part of best practices and the complexities in applying such methods in a reproducible, rigorous, and topic-specific manner to a heterogeneous data set.