Post-transition-state bifurcation (PTSB) refers to a phenomenon in which one single transition-state (TS), so-called ambimodal TS, leads to the formation of multiple products without encountering local minima on the potential energy surface (PES) . The ambimodal selectivity 2 caused by PTSBs has been observed in many chemical reactions ranging from pericyclic reactions, nucleophilic reactions, organometallic catalysis, to biosynthetic transformations . To investigate the impact of PTSB on product ratio, direct dynamics trajectory simulations have been extensively employed, from which ambimodal selectivity is predicted by counting the distribution of trajectories that fall into different product regions. Given the high computational demand of trajectory simulations, analytical models, statistical models, and machine learning models have been developed to predict ambimodal selectivity based on the features of transition state structure (e.g., distribution of geometry and momentum ), valley ridge inflection point, or topology of potential energy surface . In addition, variational transition state theory (VTST) has been employed to characterize post-TS minimum free energy path, identify dynamical bottlenecks, and explain the origin of ambimodal selectivity. Despite these substantial efforts to quantitatively predict ambimodal selectivity, one fundamental puzzle lies in how the entropy of dynamic reacting species mediates ambimodal selectivity. Entropic intermediates and entropic traps have been observed from reaction dynamics trajectories, but their contributions to PTSB remain unknown. Previously, we developed a computational method, entropic path sampling, to evaluate the change of entropy along the post-TS reaction path using reaction dynamics trajectories (Figure ). Different from VTST that evaluates entropy using harmonic approximation, EPS approach directly calculates entropy from the probability density functions of individual degrees of freedom (DoFs) based on Kirkwood superposition approximation and mutual information spanning trees approximation. EPS method holds great promise to evaluate the entropic effects of reacting species in mediating ambimodal selectivity. However, one major pitfall lies in its high computational demand. To obtain a converged entropic profile, EPS requires more than 2,000 reaction dynamics trajectories. This computational cost is 10 times more than the regular amount used for PTSB studies (e.g., 100-200 trajectories).