Accurately predicting industrial aging processes makes it possible to schedule maintenance events further in advance, ensuring a cost-efficient and reliable operation of the plant. So far, these degradation were usually described by mechanistic or simple empirical prediction models. In this paper, we evaluate wider range data-driven models, comparing some traditional stateless models (linear ke...