The modal split model is one of the steps of the classical four-step travel demand planning. Predictive, descriptive, and prescriptive modal split models are essential to make a balance between travel demand and supply. To calibrate these models, it is necessary to detect and employ influential independent variables that are related to characteristics of travel modes, individual and family attributes, zones land use, etc. In previous studies, researchers used the household size, the number of children, and the number of employees as independent variables to show the role of family structure on the modal split. These variables cannot discriminate between different families with different structures. This paper uses the life cycle concept to categorize families based on their structures, and the effectiveness of these new variables on modal split models is examined. For this purpose, five types of family structures are considered that differences between them are based on the age of the family’s children. The Multinomial Logit model is used for mode choice modeling for different trip aims. The mode choice model has been calibrated using the origin-destination data of Qazvin-Iran. Results show the critical role of life cycle dummies in the mode choice models compared to household size, for work, educational, personal, and social- recreational trip aims. Life cycle variables are more active on the work trips mode choice model by estimating 14 significant coefficients, in a 90 percent level of significance. The number of life cycle significant coefficients is decreased to 3 for the shopping trips model.