Response surface methods for the study of multiple-agent interaction allow one to model all of the information present in full concentration-effect data sets and to visualize and quantify local regions of synergy, additivity, and antagonism. In randomized wells of 96-well plates, Aspergillus fumigatus was exposed to various combinations of amphotericin B, micafungin, and nikkomycin Z. The experimental design was comprised of 91 different fixed-ratio mixtures, all performed in quintuplicate. After 24 h of drug exposure, drug effect on fungal viability was assessed using the tetrazolium salt 2,3-bis {2-methoxy-4-nitro-5-[(sulfenylamino) carbonyl]-2H-tetrazolium-hydroxide} (XTT) assay. First, we modeled each fixed-ratio combination alone using the four-parameter Hill concentration-effect model. Then, we modeled each parameter, including the 50% inhibitory concentration (IC(50)) effect, versus the proportion of each agent using constrained polynomials. Finally, we modeled the three-agent response surface overall. The overall four-dimensional response surface was complex, but it can be explained in detail both analytically and graphically. The grand model that fit the best included complex polynomial equations for the slope parameter m and the combination index (equivalent to the IC(50) for a fixed-ratio concentration, but with concentrations normalized by the respective IC(50)s of the drugs alone). There was a large region of synergy, mostly at the nikkomycin Z/micafungin edge of the ternary plots for equal normalized proportions of each drug and extending into the center of the plots. Applying this response surface method to a huge data set for a three-antifungal-agent combination is novel. This new paradigm has the potential to significantly advance the field of combination antifungal pharmacology.