Cardiovascular disease in general, and sudden cardiac death in particular, have an enormous socio-economic burden worldwide. Despite significant efforts to improve cardiopulmonary resuscitation, survival rates remain low. Moreover, patients who survive to hospital discharge have a high risk of developing severe physical or neurological symptoms. Being able to predict outcomes after resuscitation from cardiac arrest would make it possible to tailor healthcare approaches, thereby maximising efforts for those who would mostly benefit from aggressive therapy. However, the identification of patients at risk of poor recovery after cardiac arrest is still a challenging task which could be facilitated by novel biomarkers. Recent investigations have recognised the potential of non-coding RNAs to aid in outcome prediction after cardiac arrest. In this review, we summarize recent discoveries and propose a handful of novel perspectives for the use of non-coding RNAs to predict outcome after cardiac arrest, discussing their use for precision medicine.