Triple negative breast cancers (TNBCs), lacking estrogen (ER), progesterone (PR) or Her2 receptors, are a heterogeneous group, which have an overall poor outcome, being generally higher grade and often occurring in younger women. In contrast to ER positive cancers, there are currently no good biomarkers to predict outcome and no targeted treatments for TNBC. Hormone receptors play a pivotal role in breast cancer: ER and PR are favourable outcome markers, and ER-targeted treatments are standard of care. They are members of the nuclear receptor superfamily (NRs) of transcription factors, which mediates the signals of endogenous and exogenous ligands, including hormones, metabolic factors and xenobiotics. NRs have high therapeutic potential because their ligands are often lipophilic, passing easily into cells. Moreover, numerous synthetic analogues already exist targeting specific NRs, many of which are therapeutically approved in other clinical settings. We investigated NR gene expression in a large meta-dataset of TNBC and discovered that many of the NR family members are expressed in subsets of TNBC and that NR expression classified TNBCs into good and poor outcome groups. We screened a panel of drugs targeting the NRs that were most strongly associated with outcome in TNBC, to ask whether any could act as novel treatments combined with existing therapies. We showed that the fibrate class of lipid lowering drugs dramatically halted the growth of TNBC cells in our culture model, suggesting that these clinically approved drugs may have some benefit in treating TNBC. We also developed a precision medicine NR gene signature-based test, which predicts a patient’s risk of relapse when treated with existing therapies. This new test will assist clinicians when deciding the best treatment plan for their patients with TNBC and may allow some patients with low risk TNBC to be spared damaging cytotoxic chemotherapies.