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Using conventional solvers, the simulation of a complex and large system such as the automotive paint ovens can be quite time consuming - of the order of a several weeks or even months. A reduced order computational model of the oven that can predict thermal distribution quicker is useful in performing optimization studies and in directing finer design changes to the oven and the car body. This research focuses on the development of such a lumped capacitance thermal model (defined here in as the reduced order model: ROM) for predicting the heat of curing of an object that is inside an industrial oven. Essentially, the heat transfer modes are computed through a set of linear ordinary differential equations, by conceptualising the the physical object is conceptualised as a series of inter-connecting nodes that are linked by thermal resistors.