This paper reports the first application of the multicriteria decision making methods, PROMETHEE and GAIA, to indoor and outdoor air quality data. Fourteen residential houses in a suburb of Brisbane, Australia were investigated for 21 air quality-influencing criteria, which included the characteristics of the houses as well as the concentrations of volatile organic compounds, fungi, bacteria, submicrometer, and supermicrometer particles in their indoor and outdoor air samples. Ranking information necessary to select one house in preference to all others and to assess the parameters influencing the differentiation of the houses was found with the aid of PROMETHEE and GAIA. There was no correlation between the rank order of each house and the health complaints of its occupants. Patterns in GAIA plots show that indoor air quality in these houses is strongly dependent on the characteristics of the houses (construction material, distance of the house from a major road, and the presence of an in-built garage). Marked similarities were observed in the patterns obtained when GAIA and factor analysis were applied to the data. This underscores the potential of PROMETHEE and GAIA to provide information that can assist source apportionment and elucidation of effective remedial measures for indoor air pollution.