Simulations of magnetization processes have significant meaning in regards to both scientific and practical points of view [1,2,3,4,5,6]. The observed progress in technologies utilizing magnetic materials requires new magnets with unique properties optimized for different applications. What is more, a permanent demand for soft and hard magnets with ultimate characteristics can be observed [7,8,9,10,11]. Designing such systems should include modeling of the magnetization processes using computer simulations, which enables the searching for and testing of their properties in a pre-lab state. In this field, two main directions can be indicated, i.e., simulations based on the Landau equation [12,13,14] or Monte Carlo (MC) rules [15,16,17,18,19]. Both methods have advantages and disadvantages depending on the intended use of the considered magnetic system. The first approach is rather dedicated to continuous large-scale systems in which phenomena occurring at the atomic level are represented by some average volumetric parameters. On the other hand, the MC simulation methods are based on inter-atomic properties, and therefore, modeling of mesoscopic systems results in significant consumption of computational resources. This problem can be solved using parallelization of the MC algorithm [20,21]. Unfortunately, in order to study magnetization processes of ferromagnetic systems, it is necessary to utilize one of the cluster MC methods, and therefore, the possible parallelization is rather problematic. One can imagine a situation in which a node in a system represents a “super-cell” instead of single spin or magnetic moment. In this way, the analyzed system can be enlarged by means of the super-cell size. The question is how to ensure thermodynamic as well as energetic equivalence between the initial (with spins) and the enlarged (with super-cells) systems, transferring properties on the atomic level to the approach based on the finite element method.