A hybrid model for predicting corrosion in a system integrates a physics-based model developed using laboratory data and a machine-learning model developed using in-field data. Said hybrid model may be used, for example, in methods by: determining a physics-based measurement of corrosion using a physics-based model for a fluid's corrosion of a substrate based, at least in part on, lab-based measurements; determining a machine learning-based measurement of corrosion using a machine learning-based model for the fluid's corrosion of the substrate based, at least in part on, in-field-based measurements; and applying an ensemble method to the physics-based measurement of corrosion and the machine learning-based measurement of corrosion to yield an estimated measure of corrosion of the substrate. The hybrid model may be applied to corrosion mechanisms that occur in, for example, hydrocarbon transportation systems, hydrocarbon production systems, hydrocarbon refining systems, and alkylation systems.