Background: Pheochromocytomas and paragangliomas (PPGL) have up to 20% rate of metastatic disease that cannot be reliably predicted. This study prospectively assessed whether the dopamine metabolite, methoxytyramine, might predict metastatic disease, whether predictions might be improved using machine learning models that incorporate other features and how ML-based predictions compare to predictions by specialists in the field. Methods: In this machine learning modelling study we used cross-sectional cohort data from the PMT trial, based in Germany, Poland, and the Netherlands, to prospectively examine the utility of methoxytyramine to predict metastatic disease in 267 patients with pheochromocytomas and paragangliomas and positive biochemical test results at initial screening. Another retrospective dataset from 493 patients with PPGL enrolled under clinical protocols in National Institutes of Health (00-CH-0093) and the Netherlands (PRESCRIPT trial), was used to train and validate machine learning models ...