Ecosystems are highly valuable as a source of goods and services and as a heritage for future generations. Knowing their condition is extremely important for all management and conservation activities and public policies. Until now, the evaluation of ecosystem condition has been unsatisfactory and thus lacks practical implementation for most countries. We propose that ecosystem integrity is a useful concept that can be used to evaluate ecosystem condition through data science and machine learning. Based on a three tier (contextual, instrumental and hidden) model and a Bayesian network approach, we used field and remote sensing data to estimate the integrity of terrestrial ecosystems per 250 m in Mexico.