Abstract: The Kuroshio intrusion (KI) has significant implications for the dynamics and ecological environment of the South China Sea (SCS). This study employs the satellite altimetry data and geostrophic streamline morphology of the Kuroshio to quantify the spatiotemporal changes of the looping and leaking intrusion transport of the Kuroshio into the SCS. The study also uses statistical methods to analyze the interannual and decadal variability of the KI in relation to the Pacific Decadal Oscillation (PDO) and the El Niño-Southern Oscillation (ENSO). The result indicates that: ①On the interannual timescale, when the PDO is in its negative phase, the ENSO activity is negatively correlated with the volume of the looping intrusion, and the correlation coefficient was −0.55, which means that as Niño3.4 index increases (decreases), the looping intrusion weakens (enhances). This is due to the regulatory role of ENSO on the zonal wind stress at the Luzon Strait, the change of the invasion transport is caused by the change of the Asian monsoon. When the PDO is in positive phase, there is no significant correlation between the ENSO and the looping intrusion, the correlation coefficient between them is merely −0.07. The PDO is positively correlated with the transport of the leaking intrusion, the correlation coefficient was 0.5, which may be related to the position changes of the North Equatorial Current bifurcation caused by the influence of PDO on the wind stress curl over the subtropical gyre. ②On the decadal timescale, during the warm (cold) phase of PDO, both the transport of looping and leaking intrusion increase (decrease), the correlation coefficients with PDO were 0.57 and 0.72, respectively, leading to an enhancement (weakening) of the KI into the SCS. This is closely related to the decadal changes in the wind stress curl caused by the PDO in subtropical region, which affects the location of the North Equatorial Current bifurcation, and then affects the change of the KI. The study quantifies and statistically analyzes the transports of the KI with different forms and their interannual and decadal variability, which can promote a better understanding of the mechanisms of the KI into the SCS and improve the predictability of such events.