<p>This paper explores the dynamics of an eco-epidemiological prey-predator model, identifying four equilibria and analyzing their behaviors under various parameter settings. We investigate four bifurcations, Fold, Andronov-Hopf, Fold-Hopf, and Bogdanov-Takens, using central manifold and normal form calculations to assess their impact on system stability. We examine the system’s transitions between periodic and chaotic states by employing tools such as time series analysis, Lyapunov exponents, bifurcation diagrams, Poincare sections, and phase space reconstruction. We discover a self-excited attractor and highlight the system’s sensitivity to initial conditions and parameter changes. Additionally, we demonstrate the high accuracy of a Radial Basis Function Neural Network in modeling the system’s complex dynamics. This research advances our understanding of nonlinear dynamics and bifurcation theory in eco-epidemiological systems, offering valuable computational tools for future studies in ecological epidemiology and mathematical biology.</p>