As the primary input to coronal and solar wind models, global estimates of the solar photospheric magnetic field distribution are critical to space weather forecasting. These global magnetic maps are essential for accurate modeling of the corona and solar wind, which is vital for gaining the basic understanding necessary to improve forecasting models needed for Air Force operations. In this paper, we describe our efforts and progress toward developing the Air Force Data Assimilative Photospheric flux Transport (ADAPT) model. ADAPT incorporates the various data assimilation techniques, including an ensemble Kalman filter, with a photospheric magnetic flux transport model. The flux transport model evolves the magnetic flux on the Sun using relatively well understood transport processes when observations are not available and then updates the modeled flux with new observations using data assimilation. The data assimilation rigorously takes into account model and observational uncertainties, as well as accounting for regional correlations. The flux transport model and the data assimilation codes have been fully coupled and are now being extensively verified. After verification the model output will then be compared directly with observations (e.g., photospehric field strength and polarity, coronal hole boundaries, polar field strength, and ultimately solar wind). Anticipated outcomes of the ADAPT model include improvement in: 1) the estimation of solar corona and polar fields, 2) understanding the nature and behavior of solar super granular diffusion and meridional flows over the solar cycle, and 3) modeling and forecasting the solar wind near Earth.