Example Concept: One effective approach is using SHAP (SHapley Additive exPlanations) values, which quantify the contribution of each feature to the model's predictions. SHAP values are based on cooperative game theory and provide a unified measure of feature importance across different model types. By visualizing SHAP values, data scientists can gain insights into how individual features influence predictions, thus enhancing model interpretability without modifying the model itself.