Abstract Building performance simulation [BPS] tools are important in all design stages. However, barriers such as time, resources, and expertise inhibit their use in the early design stages. This study aims to develop, as part of decision-support framework, metamodels to assess the thermal discomfort in a naturally ventilated Brazilian low-cost house during early design. The metamodels predict the degree-hours of discomfort by heat and/or by cold as a function of design parameters for three Brazilian cities: Curitiba, Sao Paulo, and Manaus. The key design parameters, related with passive design strategies, are building orientation, shading devices position and dimensions, thermal properties of the walls and roof, window-to-wall ratio, and effective window ventilation area. The method consists of three main stages: (i) baseline model development; (ii) Monte Carlo simulation; (iii) multivariate regression. Overall, the metamodels showed R2 values higher than 0.95 for all climates, except the ones predicting discomfort by heat for Curitiba (R2 =0.61) and Sao Paulo (R2 =0.75). The proposed metamodels can quickly and accurately assess the thermal performance of naturally ventilated low-cost houses. They can be used to guide professionals during the early design stages, and for educational purposes in building design pedagogy.