Surrogates that can represent complex real fuels have been widely used to model combustion processes in practical applications. To formulate surrogates that successfully mimic the spray combustion phenomenon of real fuels, both physical and chemical properties need to be properly matched between a real fuel and its surrogate. The surrogate formulation requires a variety of mixing rules to accurately estimate different properties of a surrogate mixture based on its composition. The present work provides a methodology to form surrogates for kerosene fuels used in aero-engine combustors, with a special focus on the emulation of sooting tendency. A nonlinear regression method is proposed to predict the threshold sooting index (TSI) for the surrogate mixtures. Along with other mixing rules for predicting molecular weight, density, viscosity, H/C ratio, and lower heating value, two surrogates with three and five components based on a surrogate palette of n-dodecane, n-tetradecane, isooctane, decalin, and 1,3,5-trimethylbenzene are formed for each of the two kerosene fuels. The results show that all the surrogates are in good agreement with their respective target fuels in terms of the target fuel properties. Some discrepancies in viscosity are observed for the five-component surrogates because of their inclusions of decalin that has a substantially higher viscosity compared to other components. As for sooting tendency, the proposed nonlinear method has a much higher accuracy in predicting the measured TSI than the conventional linear method. In addition, the spatially resolved soot volume fraction profiles in diffusion flames show that the surrogates formed through the nonlinear method capture the overall flame sooting characteristics of the target real fuels, further demonstrating the appropriateness of the nonlinear TSI prediction method for surrogate formulation.