The improvement of surface layers of structural steel components is of great importance in mechanical engineering, as failure for highly stressed technical components, as e.g., the formation of fatigue cracks or oxidization, initiates primarily at the very surfaces. Here, surface hardening heat treatments [1] provide a suitable tool to increase wear and fatigue strength. Among the multitude of surface hardening processes, [1] laser surface hardening became increasingly popular in the past few decades, even more so with the development of High-Power Diode Lasers (HPDL). [2][3][4] The process is characterized by the precise and local heating of a steel workpiece using a focused laser beam, thereby austenitizing the process zone, followed by rapid self-quenching through heat conduction into the surrounding cold material and hence martensitic hardening. This surface hardening is accompanied by the formation of favorable residual stress states, i.e., predominantly compressive stresses, inside the process zone. The advantages of laser surface hardening over other steel hardening processes are i) the minimal distortion due to the fast and precise heat input, ii) the omitted requirement for a secondary quenching medium, and therefore, a high and flexible automation capability, and iii) the reduced environmental impact due to a lower power consumption. A brief description and explanation of the laser hardening process was given by Ion. [5] A lot of research was already done on laser surface hardening, mostly focusing on the numerical process prediction of the hardening result, e.g., hardening depth, width, and degree. [6][7][8][9][10] Only minor interest was given to the formation of residual stresses induced by laser surface hardening. De la Cruz et al., [11] for example, showed the positive effect of laser surface hardening on fatigue resistance in comparison with quenched and tempered material states due to the induced compressive residual stresses. In literature, there are multiple different numerical models which allow the prognosis of transient process stresses and resulting residual stresses, e.g., studies by Liverani et al., Müller et al., and Bailey et al.,[9,12,13] at low cost and effort. However, in our judgment, the transient process stress and residual stress prediction by