  In this study we estimate the stellar ages of LAMOST DR8 Red Giant Branch
(RGB) stars based on the Gradient Boosting Decision Tree algorithm (GBDT). We
used 2,643 RGB stars extracted from the APOKASC-2 astero-seismological catalog
as training data-set. After selecting the parameterses ([$\alpha$/Fe], [C/Fe],
T$_{eff}$, [N/Fe], [C/H], log g) highly correlated with age using GBDT, we
apply the same GBDT method to the new catalog of more than 590,000 stars
classified as RGB stars. The test data-set shows that the median relative error
is around 11.6$\%$ for the method. We also compare the predicted ages of RGB
stars with other studies (e.g., based on APOGEE), and find systematic
differences. The final uncertainty is about 15 to 30$\%$ compared to open
clusters' ages. Then we present the spatial distribution of the RGB sample
having an age determination, which could recreate the expected result, and
discuss systematic biases. All these diagnostics show that one can apply the
GBDT method to other stellar samples to estimate atmospheric parameters and
age.
