These restrictions can now be overcome with high-throughput computational chemistry which offers new avenues to elucidate reaction pathways and mechanisms through chemical reaction network (CRN) explorations. Supported by the steady increase of computing power and availability of high performance computing clusters, quantum chemistry based reaction network explorations are developing rapidly and they make extensive use of algorithms for their automated and autonomous execution. Several mechanism-exploration procedures have been implemented in recent years (see compilation in ref ). In the Software for Chemical Interaction Networks (SCINE), which we will use in this study, such CRN explorations are carried out in three principle steps. First, the reaction space is explored by searching elementary steps which interconnect the molecular structures of reactants, intermediates, transition states and products. To do so, first-principle heuristics, that is features of the electronic wave function, facilitate the generation of reaction coordinates and thus prediction of reactive sites in molecular structures for uni-and bimolecular reactions. Not only are these algorithms agnostic to the functional groups in the studied molecules, but they also allow for exploring all possible reactive combinations to obtain a comprehensive picture of the reaction network. Second, the minimum and transition-state structures and corresponding energies generated during the initial CRN explorations may require a refinement given that these explorations are typically carried out with fast electronic structure methods such as semipirical ones (e.g., xTB ) and density functional theory (DFT). These quantum chemical characterizations of the CRN can involve computationally more demanding coupled cluster (CC) methods for electronic energy calculations. Third, the obtained reaction Gibbs energies need to be evaluated modeling experimental conditions in terms of shortest reaction path to determine reaction mechanisms, and microkinetic simulations to predict the concentrations of all the compounds in the CRN. Most recent developments address the need for efficient navigation of CRN explorations and restrict the combinatorial explosion of reaction paths by allowing user-defined interventions (e.g., by expert knowledge, on-the-fly evaluation of concentration fluxes, interactive structure manipulation). The goal of this study was to evaluate how automated CRN explorations can support the elucidation of mechanisms and pathways of reactions of chemical oxidants with organic compounds and provide a conceptual basis for future applications. We focused our study on reactions of ozone with olefins in aqueous solution for purposes of both practical relevance and systematic development of the computational methodology for CRN explorations.