Two main short-cut methods for catalyst particle effectiveness factor (EF) estimation that use kinetics linearization about surface and average concentration conditions have been recently considered in the literature. The former produces simple computations with acceptable estimations for low Thiele modulus values, although negative particle concentrations can be generated. The latter is intended to improve the particle concentration profiles but at the expense of increased computations. The aim of this paper is to propose a hybrid method that combines the advantages of the two approaches to obtain EF and concentration profile estimations that are better than those of the individual ones. This is done by taking a kinetics linearization at an artificial concentration condition resulting from a type of Crank-Nicholson scheme. From a simple error analysis, it is shown that the resulting short-cut procedure displays enhanced convergence properties, which is corroborated by means of numerical computations.