Abstract: In response to the challenges associated with monitoring fracture patterns during hydraulic fracturing in deep coal mines and the potential information loss inherent in traditional point−based monitoring methods, this paper explores the potential and technical limitations of distributed fiber optic sensing (DFOS) technology in hydraulic fracturing monitoring. Based on the principles of fiber optic sensing, the monitoring mechanisms of Distributed Acoustic Sensing (DAS), Distributed Temperature Sensing (DTS), and Distributed Strain Sensing (DSS) are systematically reviewed. Considering the geological characteristics of coal and rock masses—such as low elastic modulus and strong heterogeneity—the applicability and limitations of different sensing technologies in fracture geometry inversion, fluid tracing, and microseismic detection are analyzed. The analysis shows that DAS is sensitive to the acoustic response generated during dynamic fracture propagation, DTS excels at tracing fluid migration pathways, and DSS provides precise characterization of the strain field near the wellbore. Thus, these three technologies exhibit significant complementarity across both temporal and spatial scales. Due to the unique mechanical properties of coal and rock, the efficiency of strain transfer to the optical fiber is relatively low. Moreover, gas−bearing coal seams strongly attenuate high−frequency acoustic waves, which limits the monitoring accuracy of individual technologies and leads to non−unique interpretation results. Multi−source information fusion is key to overcoming the inversion ambiguities associated with complex fracture networks. Future research should focus on developing low−modulus, high−friction encapsulation materials suitable for soft coal seams, constructing artificial intelligence−based weak−signal demodulation algorithms, and establishing coupled thermal–hydrological–mechanical (THM) inversion models. These efforts will contribute to achieving intelligent and precise monitoring of hydraulic fracturing in coal mines.