Abstract: Based on the fishery data of Chilean jack mackerel (Trachurus murphyi) in the Southeast Pacific Ocean from 2012 to 2018, the geographically weighted regression (GWR) model was applied to analyze the spatial heterogeneity relationship between fishing ground distribution and environmental factors. The results show that the goodness of fit (R²) between CPUE and sea surface temperature (SST), chlorophyll a concentration (Chl-a), sea surface temperature anomaly (SSTA), sea surface height anomaly (SSHA), gear depth were 0.54, 0.48, 0.74, 0.72 and 0.46, respectively. The adjusted R² between CPUE and SST, Chl-a, SSTA, SSHA, gear depth were 0.34, 0.36, 0.58, 0.59 and 0.42, respectively. The Akaike information criterion (AIC) between CPUE and SST, Chl-a, SSTA, SSHA, gear depth were 1 022.08, 2 321.95, 2 268.07, 2 201.93 and 2 675.07, respectively. SSTA is more influential than the other environmental factors on the spatio-temporal distribution of Chilean jack mackerel fishing grounds in the Southeast Pacific Ocean. The GWR model is used to explore the "hot spot" zones and can provide a scientific basis for the production of Chilean jack mackerel.