This study seeks to explore the predictors of female project managers’ salary in the construction industry, and to analyze their impacts on determining the salary. Experience, age, marital status, motherhood, having children at home, and the number of children at home were selected as the independent variables. Snowball sampling method was used to identify the potential participants, and surveys were sent to participants to collect data. 206 responses were collected and comprehensive descriptive and statistical analyses were performed on the responses. The study finds that experience and age have a positive relationship with female project managers’ salaries. Being married and having children at home have significant negative impacts on female project managers’ salaries. A regression model is also built to determine the prediction power of variables. Fifty-one percent of the variability in salary can be accounted for by the variables included in this model.