A specialized data-mining algorithm has been developed using wide-field photometry catalogs, enabling systematic and efficient searches for resolved, extremely low surface brightness satellite galaxies in the halo of the Milky Way (MW). Tested and calibrated with the Sloan Digital Sky Survey Data Release 6 (SDSS-DR6) we recover all 15 MW satellites recently detected in SDSS, six known MW/Local Group dSphs in the SDSS footprint, and 19 previously known globular and open clusters. In addition, 30 point-source overdensities have been found that correspond to no cataloged objects. The detection efficiencies of the algorithm have been carefully quantified by simulating more than three million model satellites embedded in star fields typical of those observed in SDSS, covering a wide range of parameters including galaxy distance, scale length, luminosity, and Galactic latitude. We present several parameterizations of these detection limits to facilitate comparison between the observed MW satellite population and predictions. We find that all known satellites would be detected with >90% efficiency over all latitudes spanned by DR6 and that the MW satellite census within DR6 is complete to a magnitude limit of M_V –6.5 and a distance of 300 kpc. Assuming all existing MW satellites contain an appreciable old stellar population and have sizes and luminosities comparable with currently known companions, we predict lower and upper limit totals of 52 and 340 MW dwarf satellites within ~260 kpc if they are uniformly distributed across the sky. This result implies that many MW satellites still remain undetected. Identifying and studying these elusive satellites in future survey data will be fundamental to test the dark matter distribution on kpc scales.