An information theory-based methodology has been applied to the multiproperty modeling of solution properties. Under this framework, a practical application on a set of binary solutions formed by dimethyl carbonate and six even saturated hydrocarbons (from C6 to C16) is carried out. A dense experimental database is generated composed of volumetric and energetic properties (from mixing processes), and phase equilibria, in order to disambiguate some discrepancies showed by the literature data, mainly for the binary with dodecane. The experimental information is modeled with a semiempirical equation for g(E), and with the PCP-SAFT equation of state, which presents a solid theoretical basis. The optimal parameterizations are sought using the precision-complexity binomial whose aim is to increase the validity range of the set of parameters obtained. The Akaike Information Criterion is used to search the best parameterizations, that is, the appropriate number of parameters (complexity) and their best values (precision). With regard to the suitability of the precision-complexity methodology on the models tested, the following is concluded: with PCP-SAFT, precise and reliable estimates are obtained; for the g(E) model, the proposed approach is essential to control the number of free parameters and to preserve the stable numerical behavior in a wide range of conditions.