Achieving long-term catalyst stability remains a grand challenge in catalysis. A recent study combines neural-network potential-based molecular dynamics simulations with decision tree-based interpretable machine learning, unveiling crucial support properties that guide the rational design of sinter-resistant platinum catalysts.