Wastewater quality is usually assessed using physical, chemical and microbiological tests, which are not suitable for online monitoring, provide unreliable results, or use hazardous chemicals. Hence, there is an urgent need to find a rapid and effective method for the evaluation of water quality in natural and engineered systems and for providing an early warning of pollution events. Fluorescence spectroscopy has been shown to be a valuable technique to characterize and monitor wastewater in surface waters for tracking sources of pollution, and in treatment works for process control and optimization. This paper reviews the current progress in applying fluorescence to assess wastewater quality. Studies have shown that, in general, wastewater presents higher fluorescence intensity compared to natural waters for the components associated with peak T (living and dead cellular material and their exudates) and peak C (microbially reprocessed organic matter). Furthermore, peak T fluorescence is significantly reduced after the biological treatment process and peak C is almost completely removed after the chlorination and reverse osmosis stages. Thus, simple fluorometers with appropriate wavelength selectivity, particularly for peaks T and C could be used for online monitoring in wastewater treatment works. This review also shows that care should be taken in any attempt to identify wastewater pollution sources due to potential overlapping fluorophores. Correlations between fluorescence intensity and water quality parameters such as biochemical oxygen demand (BOD) and total organic carbon (TOC) have been developed and dilution of samples, typically up to ×10, has been shown to be useful to limit inner filter effect. It has been concluded that the following research gaps need to be filled: lack of studies on the on-line application of fluorescence spectroscopy in wastewater treatment works and lack of data processing tools suitable for rapid correction and extraction of data contained in fluorescence excitation-emission matrices (EEMs) for real-time studies.