This work describes a method for accurate and dynamic payload estimation for mobile hydraulic excavators. It comprises of a base analytical model that expresses the payload as a function of joint torques and motion parameters, complimented using a machine-learning model that uses a data-driven approach to significantly increase the accuracy of the overall payload estimate. Measurements performed on a target excavator validate the accuracy of the method under real world conditions.