Bacterial pneumonia remains a significant global health challenge, necessitating rapid and accurate diagnostic methods for effective treatment. This review comprehensively examines the current status and future perspectives of electrophoretic techniques in bacterial pneumonia detection, highlighting their potential to address limitations of conventional diagnostic methods. Recent advances in electrophoretic platforms, including capillary electrophoresis, gel electrophoresis, and microchip-based systems, have demonstrated promising capabilities for rapid pathogen identification and characterization. These techniques offer unique advantages in terms of separation efficiency, multiplexing capability, and analytical speed. Integration with mass spectrometry, fluorescence detection, and immunological methods has further enhanced their diagnostic potential. Notable developments include automated systems capable of simultaneous detection of multiple pathogens, point-of-care devices for resource-limited settings, and sophisticated data analysis approaches incorporating machine learning algorithms. Current applications range from direct pathogen detection in clinical samples to antibiotic resistance profiling and strain typing. The review also addresses critical challenges, including sensitivity limitations, standardization requirements, and implementation costs. Emerging trends in miniaturization, microfluidic integration, and advanced materials development suggest promising directions for improving diagnostic capabilities. Recent studies have demonstrated successful applications in detecting common pneumonia-causing pathogens such as Streptococcus pneumoniae, Haemophilus influenzae, and Mycoplasma pneumoniae, with reduced analysis times and enhanced accuracy compared to traditional methods. The integration of artificial intelligence and automated analysis systems has further improved result interpretation and diagnostic reliability. While technical and economic challenges persist, ongoing developments in electrophoretic techniques show potential for transforming bacterial pneumonia diagnosis, ultimately contributing to improved patient outcomes through more rapid and precise pathogen identification.