The determination of thermophysical material properties is an important aspect for modern day technology. This can be attributed to the rapid advance of numerical simulations throughout the industries and the generally rising academic interest in thermodynamics, as a branch of physics, itself. Many common legacy testing approaches for the acquisition of such properties are slow, or not used to their fullest potential - either by relying on steady-state techniques, or lacklustre instrumentation. Only obtaining the bare minimum of data seems wasteful as high-performance computing becomes broadly available; and data-driven models, machine learning and artificial intelligence systems achieve new breakthroughs by the day. This thesis focuses on the laser flash method (or “Laser Flash Analysis” – LFA), which is used to determine the thermal diffusivity of a substance. The aim is to point out how this method could readily be improved, to also provide thermal conductivity and volumetric heat capacity of a substance, which potentially could eliminate the need for other measurements and thus save time and cost. This is achieved by two different approaches: improving the instrumentation and inverse problem solving. We propose a novel model for the inverse problem and provide other conceptions, which could contribute to the solution by other means, i.e. through statistical thermodynamics. Experimental proof is given by applying these concepts on six different thermoplastic materials and comparing the results against otherwise measured properties. We also consider possible culprits of this method, specifically for polymers. We found evidence, that one of the most important influence on this measurement method are the optical properties of polymers, therefore the modification of them (i.e. by graphite coating) has to be subjected to further research. Because the accuracy and the precision of our crudely simplified model still require further improvements, we discuss possible reasons and are able to provide guidance for future adoptions.