To better understand the drivers of mental health-seeking behavior, the individual’s beliefs, attitudes, behaviors, and sociocultural identities must be considered. Such an analysis, however, is complicated by the nature of data sets detailing these factors. Features such as marital status, educational attainment, and employment status, for example, represent unordered categorical variables and require special consideration when selecting an analytical tool. Multiple correspondence analysis is an underused statistical technique that allows one to achieve such a goal. In this article, we use a public-domain data set to demonstrate how multiple correspondence analysis can be used to analyze the relationships between men’s beliefs and behaviors about masculinity, their mental health-seeking behaviors (approximated by the indicator “how often would you say you see a therapist?”), and their intersectional identities. Diverse masculinity ideology profiles of respondents are identified revealing a significant degree of intersectional disparities between groups of men where sexual orientation, age, or being married appear to be highly determinant variables in some of the obtained profiles. These profiles of respondents, and their relationships to the studied variable, might serve as the basis for better-informed public health communications.