The PACE framework combines data-driven predictive models with symbolic reasoning to generate realistic counterfactual explanations. It solves the common problem of unrealistic recommendations by enforcing domain knowledge and intervention constraints. This neuro-symbolic approach ensures suggested input changes are actually actionable. Practitioners can now produce explanations that respect real-world constraints rather than purely mathematical minima.