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The design of temperature controllers is impaired by the limited accuracy of the models employed for thermal systems, which are commonly estimated from uninformative data, such as step responses, due to the restrictive experimental design connected to the long duration of the experiments. This paper focuses on modelling an industrial convection oven following different rationales. Three continuous-time models are proposed and compared: a grey-box parametric thermal network model, a black-box parametric first order lag plus time delay model, and a black-box non-parametric model based on reproducing kernel Hilbert spaces. These are all estimated and validated on step response experimental data. Lastly, the pros and cons of each model are highlighted.