Idiopathic pulmonary fibrosis (IPF), the most common fibrotic lung disease, is a chronic disease of unknown etiology with a very high mortality. Personalized medicine focuses on the use of the individual's molecular and 'omic' (i.e., genomic, epigenomic and proteomic) information to direct more efficient and cost-effective strategies for prevention, diagnosis, outcome prediction and treatment of diseases. In this review, we describe the use and promise of applying 'omic' technologies to the familial and sporadic forms of IPF as a means to personalize diagnosis and outcome prediction in IPF. The validation and implementation of such approaches will be crucial to personalize IPF patient care, prioritize lung transplant and stratify patients for drug studies, as well as, in the future, predict response to therapies as they emerge.