Thermal bridging through cold-formed steel (CFS) channels can be substantially reduced by introducing staggered slots in the channels’ webs. The perforation size and pattern significantly affect the elastic shear buckling and ultimate loads of the channels in shear, which must be considered in the design. This paper proposes new models for accurate estimations of the shear buckling and ultimate loads derived from an extensive database by employing gene expression programming (GEP). The model constructions involve various dimensional parameters, types of boundary conditions, and the yield strength of the channels. The proposed GEP models, in the form of transparent mathematical expressions, provide reasonable prediction accuracy comparable to published descriptive equations. However, the GEP models are simpler than the existing equations and do not require additional advanced computations, as the existing equations do, to obtain the elastic shear buckling and ultimate shear loads. LRFD resistance and ASD safety factors for the proposed GEP model were determined in accordance with AISI S100-16 w/S2-20. Based on the presented information, the GEP models are recommended for estimating the elastic shear buckling and ultimate loads of CFS channels with staggered slotted web perforations in shear.