We investigate a class of conditional McKean–Vlasov stochastic differential equations with jump components and Markovian regime-switching, thereby extending classical mean-field frameworks to encompass discontinuous perturbations and environment-dependent dynamics. The models describe interacting particle systems whose evolution depends not only on the individual state and stochastic perturbations, but also on the conditional distribution of the system given an underlying filtration, providing a mathematically natural setting for partial information, common noise effects, and regime-driven interactions.

A comprehensive analysis of well-posedness, stability, and regularity is developed, revealing the delicate interaction between Poisson jump mechanisms, regime-switching dynamics, and conditional mean-field effects. A central contribution is the derivation of first- and second-order differentiability properties of the solution flow with respect to the probability measure, carried out through Lions’ differential calculus on the Wasserstein space.

Furthermore, we show that the conditional McKean–Vlasov dynamics induce a novel class of nonlocal systems of partial integro-differential equations with terminal conditions. Under appropriate structural and regularity assumptions, we establish a probabilistic representation of the unique classical solutions of these systems via an extended Feynman–Kac-type formula.

These results provide a rigorous and unified connection between conditional stochastic particle systems and their associated analytical equations, significantly enriching the theory of mean-field models with jumps and switching. The framework opens new avenues for applications in areas such as systemic risk, neural network modeling, and controlled interacting systems under uncertainty.