Catalytic foams represent a promising alternative to conventional fixed-bed reactors in many applications in the chemical and process industry. Designing and planning of foam reactors can be supported by computational fluid dynamics (CFD) simulations. In this contribution we present a fully automatic workflow (catalytic Foam Modeler: catFM) with which it is possible to model a realistic foam structure ready for CFD simulations without using data from time consuming image analysis. The modeler is based on a random distribution of points in space followed by the Voronoi tessellations. It utilizes common foam characteristics, i.e., porosity, specific surface area and strut dimensions, as input parameters to generate artificially the foam structure. Typical morphological parameters such as specific surface area, as well as pressure drop predictions can be reproduced with a good accuracy. Finally, the performance of the tool catFM is illustrated by modeling a catalytic partial oxidation reformer of methane in a foam coated with a rhodium catalyst. Two sets of simulations are performed, one with a fixed surface temperature obtained from experiments, the other takes heat transfer inside the solid material into account. On the surface a detailed reaction mechanism is implemented. For both cases, the experimental species profiles can be well reproduced. However, only the second set allows a flexible utilization without knowing the temperature profile a priori. With this modeler it is possible to plan and design catalytic foams by predicting temperature and species concentrations without relying on transport correlations. (C) 2015 Elsevier B.V. All rights reserved.