This paper addresses the design of surfactant solutions with optimal values of macroscopic properties for a particular application. A theoretically rigorous treatment is adopted to link structural parameters such as surfactant head group size, tail length, and polarity with intermediate fundamental solution properties determining the size, shape and surfactant concentration at which micelles form. Correlations, using fundamental solution properties as descriptors, are then employed to bridge the remaining gap to macroscopic properties of interest such as the HLB, emulsivity, detergency and foaming stability. An inner optimization stage minimizes the Gibbs free energy of solution to identify the fundamental solution properties while an outer optimization stage determines the surfactant molecular structure that optimizes the suitability of a surfactant for a particular application expressed in terms of macroscopic variables. The proposed theoretical, algorithmic and computational framework is illustrated with a simple example.