Real-time probabilistic seismic hazard assessment (PSHA) was developed in this study in consideration of its practicability for daily life and the rate of seismic activity with time. Real-time PSHA follows the traditional PSHA framework, but the statistic occurrence rate is substituted by time-dependent seismic source probability. Over the last decade, the pattern informatics (PI) method has been developed as a time-dependent probability model of seismic source. We employed this method as a function of time-dependent seismic source probability, and we selected two major earthquakes in Taiwan as examples to explore real-time PSHA. These are the Meinong earthquake (ML 6.6) of 5 February 2016 and the Hualien earthquake (ML 6.2) of 6 February 2018. The seismic intensity maps produced by the real-time PSHA method facilitated the forecast of the maximum expected seismic intensity for the following 90 d. Compared with real ground motion data from the P-alert network, our seismic intensity forecasting maps showed considerable effectiveness. This result indicated that real-time PSHA is practicable and provides useful information that could be employed in the prevention of earthquake disasters.