PySurf is a framework with a powerful toolbox to treat and automatize many tasks in computational chemistry. In this work, PySurf is used to implement the Landau-Zener surface-hopping scheme for nonadiabatic dynamics simulations. In surface-hopping simulations the computationally most expensive part is the large number of electronic structure calculations, that need to be performed for the independent trajectories. An obvious way to reduce computational costs is to use the ability of the SPP to fit surfaces based on already pre-computed electronic structure data. Similar approaches have been presented by Worth et al. for the dd-vMCG method with a modified Shepard interpolation scheme. For dynamics simulations using Tully's fewest switches surface-hopping (FSSH) algorithm, machine learning models to fit excited-state properties have been implemented. Combining Tully's approach with machine learning algorithms demands to fit non-observables, i.e. NACs. It has been shown that phase correction is necessary for the fitting of NACs in such a dynamics simulation. To overcome these circumstances, different surface-hopping algorithms that depend only on observables can be used, such as the Landau-Zener 32 or the Zhu-Nakamura schemes. The latter was combined with deep learning algorithms to successfully simulate the S 1 /S 0 transition of CH 2 NH and 6-aminopyrimidine. Recently, it has been shown that nonadiabatic dynamics simulations with the Landau-Zener algorithm and the FSSH algorithm produce very similar results. The main difference between both approaches is the way how the hopping probability from state i to state j is computed. In Tully's approach, this is done as a function of the coefficients of the electronic wavefunction and the nonadiabatic coupling vector. The Landau-Zener hopping probability, however, is given purely as a function of the energy gap (∆V ij = |V i -V j |) between the two states and its second derivative at a certain nuclear position R(t), if there is a minimum in the energy difference at time t c 54