We present a new multi-target filtering recursion for nonlinear models, termed as the central difference multi-target multi-Bernoulli (CD-MeMBer) filter. Provided that the state and measurement noises are Gaussian, Sterling's polynomial interpolation formula is used in deriving the filter under the assumption that the initial prior multi-Bernoulli multi-target density is given and each probability density is comprised of a Gaussian sum. The tracking performances verify the effectiveness of the proposed CD-MeMBer filter.