Transportation planning has been shifting from an emphasis on capacity expansion to issues like travel management, social equity and environmental justice, quality of life, energy sustainability, and environmental concerns. The trip-based models are not adequate for reflecting these subjects even if they have served the planning needs of metropolitan areas for many years. The activity-based models, on the other hand, are capable of providing estimates of travel demand under a wide range of scenarios at a disaggregate level.rnAddis Ababa is currently experiencing high urbanization rates. If this issue is not addressed properly, traffic delays and congestion caused by urbanization will have huge impacts on the environment due to noise and air pollutions. Studying the travel behavior of the residents of Addis Ababa is vital in trying to address the adverse effects of urbanization. In this research, the travel behavior and travel pattern of Bole Sub-City residents were studied.rnFor the purpose of building up an activity-based travel demand model, a discrete choice model was used. Activity diaries were distributed throughout the study area and the respondents were required to fill in their activiites for a period of two days. The results of the survey were then analyzed so as to build up the travel demand model. Daily activity pattern, time-of-day choice, and mode choice models were developed. These three models were linked with each other using a sequential Nested Logit framework. The result from the analysis showed that the daily activity pattern of work tours was accurately predicted by the model, with a goodness of fit of 0.883, as opposed to non-work tours which had a goodness of fit of 0.436. The relatively low goodness of fit value for non-work trips was attributed to the fact that over half of the surveyed population performed work activities leaving the rest of the percentage share to be distributed among school, maintenance, discretionary, and other types of tours.rnThis research can be used as a stepping stone for planners and engineers to further develop travel demand models for other sub-cities found in Addis Ababa.