Optimal Spectral Sampling (OSS) is a new approach to radiative transfer modeling which addresses the need for algorithm speed, accuracy, and flexibility. The OSS technique allows for the rapid calculation of radiance for any class of multispectral, hyperspectral, or ultraspectral sensors at any spectral resolution operating in any region from microwave through UV wavelengths by selecting and appropriately weighting the monochromatic points that contribute over the sensor bandwidth. This allows for the calculation to be performed at a small number of spectral points while retaining the advantages of a monochromatic calculation such as exact treatment of multiple scattering and/or polarization. The OSS method is well suited for remote sensing applications which require extremely fast and accurate radiative transfer calculations: atmospheric compensation, spectral and spatial feature extraction, multi-sensor data fusion, sub-pixel spectral analysis, qualitative and quantitative spectral analysis, sensor design and data assimilation. The OSS was recently awarded a U.S. Patent (#6,584,405) and is currently used as part of the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) CrIS, CMIS, and OMPS-IR environmental parameter retrieval algorithms. This paper describes the theoretical basis and development of OSS and shows examples of the application and validation of this technique for a variety of different sensor types and applications.