Estimating Ground Reaction Force (GRF) is important for deriving and understanding human gait dynamics and for the effective design of assistive devices. Accurate force estimation can lead to enhanced control strategies, promoting natural and efficient movement assistance. In this simulation study, various analytical techniques for GRF estimation are explored using an open standard gait dataset. The study began with the Smooth Transition Approach (STA), followed by the inverted pendulum model for estimating GRF during the double stance phase. The study compared multiple force estimation methods across different gait phases, ultimately exploring and improving a single model capable of predicting GRF throughout the entire gait cycle. The results indicated that one method provided high accuracy by using different equations for each stance phase, while another method offered consistent performance across the entire phase using a unified model. The methods were compared both visually and quantitatively using RMSE values to assess their performance in estimating GRF. The findings offer valuable insights into the selection and optimization of analytical models for GRF estimation, with potential applications not only in assistive device design but also in the development of physics-informed learning models.