Binary logit models are used to predict usage and understanding of owner-occupied and investor mortgages on the basis of demographic, socioeconomic and financial characteristics. The data is drawn from the 2003 ANZ Survey of Adult Financial Literacy in Australia and relates to 3,548 respondents. Factors examined include financial literacy, gender, age, ethnicity, occupation, educational level and family structure, along with household income, savings and debt. Understanding is defined in terms of knowledge of mortgage rates, fees and charges and familiarity with key mortgage terms. The results indicate that being middle-aged or a couple with children increases the likelihood of an owner-occupied mortgage, while being from a non-English speaking background, a small business owner or a skilled tradesman increases the likelihood of an investor mortgage. The evidence also suggests that understanding of mortgages is unevenly spread across mortgagees. Understanding is generally poorer for females, rural and regional households and the young, and better for professionals, the university educated and small business owners and skilled tradesmen. The area least understood is mortgage fees and charges.