An approach to predict the stability constants of coronates from the properties of solvents, cations, and crown ethers has been developed based on exploratory and neural network methods for mathematical modeling of equilibria in solutions. Exploratory (factor, cluster, discriminant, canonical, decision trees), regression, and neural network (supervised and Kohonen network) models of the stability of crown ethers (12C4, 13C4, 14C4, 15C4, 15C5, 18C6, 21C7, 24C8, B12C4, B15C5, CH15C5, CH18C6, DCH18C6, DCH21C7, DB18C6, DB21C7, DB24C8, DB27C9, and DB30C10) complexes with cations of alkali (Li+, Na+, K+, Cs+, Rb+) and alkaline-earth (Ca2+, Sr2+, Ba2+) metals in aqueous and non-aqueous (acetone, acetonitrile, dimethyl sulfoxide, methanol, pyridine, dimethylformamide, dioxane, propylene carbonate, 1,2-dichloroethane, and nitrobenzene) solutions have been developed according to the properties of solvents (diameter of solvent molecule, Kamlet-Taft parameter, Dimroth-Reichardt parameter, dielectric constant), crown ethers (Balaban topological index), and cations (cation diameter) at 298.15 K.