This study aimed to create a neck model that is efficient and can be used to simulate the effects of a rear-end collision. The model, called Efficient Neck Model 2D (ENM-2D), is a planar multibody model consisting of several bodies that represent the head and neck with the same mass and inertia properties as a 50th percentile male occupant model. The damping and non-linear spring parameters of the kinematic joints were identified through a multi-objective optimization process, which was solved sequentially. To validate the ENM-2D, the TNO-Human Body Model (TNO-HBM), a validated occupant model for rear impact, was simulated using the LAB sled test pulse (12g, ∆V = 10 km/h), and its responses were used as a reference. The Root Mean Square (RMS) of the deviations of angular positions of the bodies were used as objective functions, making this a multiobjective optimization problem. This optimization scheme considered a sequential approach of previous studies. The approach aimed to solve a single objective optimization problem for each pair of vertebrae, avoiding the computational cost of dealing with 42 design variables. Starting from the bottom vertebra to the top, and ending in the head, the sequence was repeated until it converged, ending the optimization process. The ENM-2D model was able to simulate the whiplash injury mechanism kinematics and accurately determine the injury criteria associated with head and neck injuries. It had a relative deviation of 8.3% for the head injury criteria and was 12.5 times faster than the reference model. The use of the efficient model combined with optimization methodologies for the identification of its design variables, allows its use in extensive parametric analysis to improve the design of the seat mechanisms that mitigate whiplash injuries.