This research took 5°×5° spatial resolution as a research grid to analyze the trends in abundance of skipjack tuna (Katsuwonus pelamis) resources in the Central and Western Pacific Ocean based on spatial location and to construct a prediction model. Meanwhile, the total catch sum of 144 grids within 130°E-140°W and 20°N-20°S sea areas from 1990 to 2019 were calculated, the top ten grids sea areas for analysis (accounting for 70% of the total catch in the study sea area) were selected, and the dynamic factor analysis method to reduce the 10 grids were used. We used dynamic factor analysis to downscale the time series trends of the 10 grids into two time series trends, determined the two time series trends corresponding to each of the 10 grids according to the factor loadings, explored the contribution of three key environmental factors, namely sea surface spacing, sea surface temperature and mixed layer depth, to the two trends of K. pelamis abundance using relative importance analysis, and constructed SARIMA models for each of the two time series trends to predict the abundance of K. pelamis in the Central and Western. The SARIMA model was constructed to predict the resource abundance of K. pelamis in the Central and Western Pacific Ocean in the next three years. The range of the highly productive sea area of bonito in the Central and Western Pacific Ocean was 5°S-5°N,145°-180°E; the first time series trend spatially corresponded to the sea area of 5°S-5°N,145°-160°E and the second time series trend spatially corresponded to the sea area of 0°-5°S,160°-180E°. The distribution of the two common trends in space was with 160°E as the dividing line. The seasonal variation of the two time series trends was obvious, with higher resources in the first half of the year than in the second half of the year. In recent years, the first time series trend (spatially distributed corresponding to the western equatorial Pacific Ocean) had been decreasing and the second time series trend (spatially distributed corresponding to the eastern equatorial Pacific Ocean) had been increasing. Sea surface temperature anomalies had contributed the most to bonito resources. For two common trends, SARIMA(9,1,0)(1,0,1) [12] and SARIMA(2,1,1)(1,0,1) had the smallest AIC and RMSE with good model prediction fit and high prediction accuracy, which were 607.45 and 0.86, 595.27 and 0.64, respectively. From 2020 to 2023, the growth of K. pelamis resources in the eastern equatorial Pacific Ocean was on an upward trend, while K. pelamis resources in the western equatorial Pacific Ocean would be downward. The study results provides a decision basis for corporate decisions, such as annual production arrangements, fishing entry decisions and sustainable development of bonito resources.