An organism's phenome results from expression of its genome (nature) under certain environment and management effects (nurture) and interactions between these factors, as well as measurement error. For over 30 years, DNA sequencing and genomics tools advanced to where it's now feasible to saturate genomes of segregating individuals, such that polymorphisms at nearly any position can be determined from other known positions. This is due to structure, linkage disequilibrium (LD), or linkage and is a powerful tool for genomic prediction and investigating biological phenomena. In contrast, most phenomics to date focuses on automating previously known "traits" as measurable and interpretable phenotypes; akin to focusing on measuring a single DNA marker rather than measuring an entire saturated genome. Viewing phenomics as a platform for discovery, similar to genomics, opens new methods for capturing phenomena in nature and nurture. Saturating a phenome would mean that an individual's fitness, performance, responses to environment and/or specific phenotypes could be accurately predicted in untested environments. To date, our experience with phenomic prediction for cumulative, complex phenotypes such as grain yield suggests it's possible to predict organismal performance in untested environments, possibly better than genomic methods despite less advanced tools and data. Factors limiting to saturating a phenome are evaluating enough individuals and environments, but more importantly, tools and methods to extract or "sequence" more phenomic features. Successfully saturating phenomes will impact every aspect of science and society, in biological disciplines from germplasm curators, physiologists to breeders, to education, the courtroom and policy.