Activity landscape modeling is an emerging concept to systematically characterize the structure–activity relationships of data sets. This concept, which can be extended to property landscape analysis, is a central topic in medicinal chemistry and many other scientific disciplines. Understanding the structure–activity or structure–property relationships (SAR/SPR) of data sets is a critical step before conducting statistical and predictive quantitative modeling. Computational characterization of the activity/property landscape, however, is a challenging task due to the high dependence of chemical space on molecular representation. Several numerical and graphical methods are emerging to characterize and navigate activity landscapes. This chapter focuses on the current status of activity landscape modeling with particular emphasis on the development of consensus models of the SAR/SPR of compound data sets.