Although the unconditional probability of a major earthquake in an area is extremely small, the probability can increase in the presence of anomalies that act as potential precursors. Precursor‐like anomalies of only a single type may not sufficiently enhance the probability of a large earthquake, but the probability can be substantially increased using the multielements prediction formula when independent precursor‐like anomalies of plural types are observed at the same time. Despite some illustrative applications for successful predictions in the late 1970s, this idea has seldom been applied for more than 40 yrs. This is because of the scarcity of remarkable anomalies preceding large earthquakes and a lack of extensive statistical studies on anomalies relative to large earthquakes, which prevents stable assessment estimates of probability gains. This article aims to provide an outlook for future study on these issues. I focus on evaluating the probability gains of a large earthquake using anomalies of seismic activity based on statistical diagnostic analysis. Specifically, I illustrate the evaluation methods with reference to seismic activity before the 2016 M 7.3 Kumamoto earthquakes. Furthermore, I discuss outlooks using similar and extended approaches in seismicity and other monitoring fields.