In the analysis of the long-term Radon Volume Activity (RVA) results for the year 2022, we applied the Dobrovolsky model for radon anomaly identification using METER.AC network data. The radius of the precursor occurrence zone was estimated, and a geodynamic criterion (K ≥ 2.3) was employed, where ‘K’ represents the ratio of earthquake magnitude to the logarithm of the distance from the monitoring station to the event. Anomalies were defined as changes in radon concentrations exceeding ± 2 standard deviations from the mean value. The baseline RVA level was determined before each earthquake event, accounting for various factors such as temperature, humidity, tidal effects, etc. Radon volume activity measurements were conducted using two sensor types, RD200M and AlphaSensor, with reports generated every 10 min. The results were compared with seismic events meeting the criteria of M ≥ 2.6 (42 earthquakes) within the territory of Bulgaria and M ≥ 4.2 for the near zone up to 500 km from the Bulgaria borders (6 earthquakes), all satisfying the geodynamic criterion (K ≥ 2.3) and preceded by RVA anomalies. After excluding events with missing data from the preceding period, it was observed that the majority of those examined were preceded by radon anomalies.