Designing new, technologically relevant superconductors has long been at the forefront of solid-state physics and chemistry research. However, developing efficient approaches for modeling the thermodynamics of superconducting alloys while accurately evaluating their physical properties has proven to be a very challenging task. To fill this gap, we propose an ab initio thermodynamic statistical method, the Extended Generalized Quasichemical Approximation (EGQCA), to describe off-stoichiometric superconductors. Within EGQCA, one can predict any computationally accessible property of the alloy, such as the critical temperature in superconductors and the electron-phonon coupling parameter, as a function of composition and crystal growth conditions using a few small supercells. Importantly, EGQCA incorporates directly chemical ordering, lattice distortions, and vibrational contributions. As a proof of concept, we applied EGQCA to the well-known Al-doped MgBb2 and to niobium alloyed with titanium and vanadium, showing a remarkable agreement with the experimental data. Additionally, we modeled the near-room temperature sodalite-like Y1−xCaxH6 superconducting solid solution, demonstrating that EGQCA particularly possesses a promising potential for designing in silico high-Tc superhydride alloys. Our approach enables the high-throughput screening of complex superconducting solid solutions, providing valuable insights into these systems' synthesis, thermodynamics, and physical properties.