A tour-based microsimulation approach to modeling destination choice and mode choice of San Francisco residents is presented. These models were developed as part of an overall tour-based travel demand forecasting model (SF model) for the San Francisco County Transportation Authority to provide detailed forecasts of travel demand for various planning applications. The models described represent two of the nine primary components of the SF model. Both model components consist of multiple logit choice models and include both tour-level models (which refer to the primary activity of the tour) and trip-level models (other activities on the tour). A separate model was estimated for each tour purpose, including work, school, other, and work-based. The destination choice models combine the trip attraction and trip distribution components of the traditional four-step process and use a multinomial logit specification. The mode choice models utilize a nested logit formulation to capture the similarities among sets of similar modes. The two models are linked by incorporating the mode choice utility logsum in the destination choice models; the result is equivalent to a nested structure with a mode choice nest under destination choice. It is demonstrated that the microsimulation approach easily allows the inclusion of a number of key variables in destination and mode choice models that have a significant explanatory power compared with those in traditional models. It is also shown that this approach allows estimation of the effects of tour characteristics on the choice of destination and mode using widely available data and estimation procedures.