The frequency and area of red tide in China’s coastal areas continue to increase, resulting in serious economic losses. According to the toxic characteristics of red tide, it is usually classified into three categories: non-toxic red tide, ichthyotoxic red tide and toxic red tide. Among them, paralytic shellfish poison is the main toxin produced by toxic red tide. Because of its wide distribution and strong toxicity have become one of the most harmful biological toxins. According to the different intake of paralytic shellfish poisoning, people will feel tingling or burning in various parts of the body after eating shellfish poisoning, and then they will be paralyzed or even die in a short time. Many people have died after eating shellfish. The intake of paralytic shellfish poisoning mainly depends on the concentration of paralytic shellfish poisoning algae. Therefore, it is particularly important to monitor the concentration of paralytic shellfish poison producing algae. In this paper, a quantitative analysis model of paralytic shellfish poison producing algae was established by three-dimensional fluorescence spectroscopy combined with chemometrics. Firstly, The three-dimensional fluorescence spectrum contour map of algae samples were analyzed by f-4600 fluorophotometer, including Alexandrium minimum, Gymnodinium catenatum and Alexandrium. Then, the new features of the three-dimensional fluorescence spectrum of paralytic shellfish poisoning algae were established using the emission spectrum data under different excitation wavelengths. Finally, the new feature was the input of particle swarm optimization least squares support vector machine and partial least squares regression respectively, and the quantitative analysis model of paralytic shellfish poisoning algae was made. The results showed that the quantitative analysis model established by Particle Swarm Optimization- Least Squares Support Vector Machine algorithm was generally better than the partial least squares regression algorithm when using the emission wavelength of 650~750 nm under an excitation wavelength of 460 and 530 nm. The results show that R_C=0.999 9, RMSEC=0.017 1, R_P=0.949 2, RMSEP=0.291 0. It shows that the three-dimensional fluorescence spectrum combined with the quantitative analysis model of Particle Swarm Optimization- Least Squares Support Vector Machine can effectively monitor the concentration value of paralytic shellfish poison producing algae in vivo, which provides a new online detection method for the concentration detection of paralytic shellfish poison producing algae.