This paper investigates a framework to estimate hand posture from 2D image sequence using hand landmarks identification. The acquired 2D data will be combined with known human hand model and its constraints. Important landmarks of the hand in the image were extracted and identified to specify the location of that landmarks, then they will be matched with the corresponding landmarks in the 3D model to estimate the hand posture and generate a 3D hand model. The result using real hand image sequence shows that the 3D model can move accordingly to the real hand. The framework works well on the four fingers including index, middle, ring, and little finger. The advantage of this method is that it works on hands without markers.