The present study describes an approach for the scale-bridging modeling of ferroic materials as functional elementsin micro- and nanoelectronic devices. Ferroic materials are characterized by temperature-dependent complex ordering phenomena ofthe internal magnetic, electronic, and structural degrees of freedom with several involved length and time scales. Hence, the modelling of such compounds is not straight forward, but relies on acombination of electronic-structure-based methods like ab-initio and density-functional schemes with classical particle-based approaches given by Monte-Carlo simulations with Ising, lattice-gas, or Heisenberg Hamiltonians, which incorporate material-specific parameters both from theory and experiment. The interplay of those methods is demonstrated for device concepts based on electroceramic materials like ferroelectrics and multiferroics, whose functionality is closely related with their propensity towards structural and magnetic polymorphism. In the present case, such scale-bridging techniques are employed to aid the development of an organic field effect transistor on a ferroelectric substrate generated by the self-assembly of field-sensitive molecules on the surfaces of ferroic oxides. Electronic-structure-based methods yield the microscopic properties of the oxide, the surface, the molecules, and the respective interactions. They are combined with classical particle-based methods on ascale-hopping basis. This combination allows to study the morphology evolution during the self-assembly of larger adsorbate arrays on the (defective) oxidesurface and to investigate the interplay of low-temperature magnetic ordering phenomena with the ferroelectric functionality at higher temperatures in multiferroic oxides like the hexagonal manganites. The combination ofdensity-functional data with classical continuum modelling also yielded a model Hamiltonian for the quick determination of the properties of a gate structure based on bio-functionalized carbon nanotubes.