Three-dimensional analysis of protein structures is proving to be one of the most fruitful modes of biological and medical discovery in the early 21st century, providing fundamental insight into many (perhaps most) biochemical functions of relevance to the cause and treatment of diseases. Fully realizing such insight, however, would require analysis of too many distinct proteins for thorough laboratory analysis of all proteins to be feasible, thus, any method capable of accurate, efficient in silico structure prediction should prove highly expeditious. The technique generally acknowledged to provide the most accurate protein structure predictions, called comparative modeling, has, thus, attracted substantial attention and is the focus of this chapter. Although other reviews have reported on the method development and research history of comparative modeling, our discussion herein focuses on the general philosophy of the method and specific strategies for successfully achieving reliable and accurate models. The chapter, thus, relates aspects of template selection, sequence alignment, spatial alignment, loop and gap modeling, side chain modeling, structural refinement, and validation.