Idiopathic pulmonary fibrosis (IPF) is an irreversible, debilitating, and ultimately lethal fibrosing interstitial lung disease (ILD) of unknown cause. The poor prognosis of IPF (mean survival less than 2-5 years post diagnosis), combined with its worldwide prevalence greater than all but the most common cancers, makes it a serious health problem. Thus, the need for early diagnosis is paramount. Currently, early screening is hampered by the absence of reliable screening tools, non-specific symptomology, a limited understanding of the phenotypic and genetic markers for early-stage IPF, and the potential need for invasive procedures for confirmatory diagnosis. In this study we introduce a new screening tool that requires no new diagnostic tests, may be universally administered, and does not necessarily require recognition of early symptoms by the patients or care providers. Applying novel pattern discovery algorithms on the detailed history of past medical encounters of individual patients, we leverage subtle comorbidity patterns to compute the Zero-burden Co-Morbidity Risk Score for IPF (ZCoR-IPF), which is expected to be widely, readily, rapidly and inexpensively applicable at points of care. Our algorithm is trained and validated on a large national insurance claims database (n=2,059,559). In out-of-sample validation, we demonstrate that ZCoR-IPF identifies IPF patients with an AUC approaching 84% at 4 years, ~86% at 3 years, ~87% at 2 years, and exceeding >88% at 1 year before conventional diagnosis. Our out-of-sample accuracy indicates that on average, we correctly predict the eventual IPF status 94-98 out of every 100 patients, with a positive predictive value >50% irrespective of sex at a specificity of 99%. Maximum PPV and NPV achieved are >70% and ~98% respectively. We investigate several important sub-populations, including high risk patients with known IPF co-morbidities, low risk patients who lack those indications, in older (>65 years) and younger populations, in patients who already have a diagnosis of Chronic obstructive pulmonary disease (COPD), asthma or have cardiac disorders, and for patients who are never recorded to have experienced dyspnea and thus are at a higher risk of a missed diagnosis. High performance of the ZCoR-IPF score across clinically relevant situations suggests that it may aid providers to more selectively flag patients for detailed diagnostic evaluation, substantially improving patient outcomes and quality-of-life, as well as efficiency of healthcare resource utilization. Additionally, earlier diagnosis may improve the odds of disease modifying therapy, optimal timing of a lung transplantation, and accelerate access to interventions and palliative care.