Abstract: Considering its computational efficiency and smoothness, the polynomial spline estimation of generalized partial functional linear models is studied. Under some regular conditions, the asymptotic normality of parameter estimation and the global convergence rate of slope function have been established. By simulation study, the validity of the estimation method is illustrated. At the same time, it is found that the spline estimation is superior to the functional principal component estimation while the true slope function is smooth and can not be expressed as a linear combination of a few eigenfunctions.