Nowadays, activity-based modeling has attracted considerable attention compared with traditional four-step models due to its numerous advantages. Given the importance of public transportation, applying an activity-based approach to public transportation users to accurately examine their behavior has gained particular significance. The present study aims to apply the activity-based approach to public transportation users. Accordingly, selected activity-based sub-models, including the number of activities per tour and the duration of activities within the tour, were examined in the daily activity pattern of public transportation users. Data were collected through a field survey of 500 public transportation users in Tehran. An ordered logit model, with a McFadden pseudo-R² of 0.362, was used to model the number of activities per tour, while another ordered logit model, with a McFadden pseudo-R² of 0.572, was employed to model activity duration within the tour. Results showed that tour duration (0.301), education (0.211), mandatory activity type (-1.34), and tour start time (-0.208) significantly affected the number of activities within the tour. Furthermore, mandatory activity type (3.74), the number of activities per tour (0.386), discretionary activity type (0.689), and tour start time (-0.246) significantly affected activity duration within the tour. Marginal effects analysis showed that tour duration, with a coefficient of 0.05, had the greatest effect on increasing the probability of undertaking three activities within a tour. In contrast, tour start time, with a coefficient of 0.123, had the greatest effect on increasing the probability of undertaking one activity within a tour. Moreover, mandatory activities, with a coefficient of 0.342, had the greatest effect on increasing the probability of activity durations of 10 to 12 hours. The findings demonstrate that individual, occupational, and temporal variables play a determining role in the daily activity-travel pattern of public transportation users and can assist urban planners in developing more effective policies.