Hydrogen is an essential commodity in any industrialized society, and its importance will continue to increase with current efforts to decarbonize the industrial and transportation sector. While conventional hydrogen production itself causes greenhouse gas emissions, methane pyrolysis provides a scalable alternative. However, operating temperatures above 1300 K are too high for industrial hydrogen production via methane pyrolysis. Thus, a major scientific goal is to find a catalyst material that lowers operating temperatures, making methane pyrolysis economically viable. In this work, we derive a model that provides qualitative comparison of possible catalyst materials. The model is largely based on calculations of adsorption energies using density functional theory. Thirty different elements were considered. Results show that adsorption energies of intermediate molecules in the methane pyrolysis reaction correlate linearly with the adsorption energy of carbon. Moreover, the adsorption energy increases with decreasing group number in the d-block of the periodic table. For a temperature range between 600 and 1200 K and a normalized partial pressure range for H2 between 10e¿1 and 10e¿5, a total of seventeen different materials were found to be optimal catalysts at least once. This indicates that catalyst selection and reactor operating conditions should be well matched. The present work establishes the foundation for future large-scale studies of surfaces, alloy compositions, and material classes using machine learning algorithms.