A new approach for performing automatic differentiation (AD) of computer codes that embody an iterative procedure, based on differentiating a single additional iteration upon achieving convergence, is described and implemented. This post-convergence automatic differentiation (PAD) technique results in better accuracy of the computed derivatives, as it eliminates part of the derivatives convergence error, and a large reduction in execution time, especially when many iterations are required to achieve convergence. In addition, it provides a way to compute derivatives of the converged solution without having to repeat the entire iterative process every time new parameters are considered. These advantages are demonstrated and the PAD technique is validated via a set of three linear and nonlinear codes used to solve neutron transport and fluid flow problems. The PAD technique reduces the execution time over direct AD by a factor of up to 30 and improves the accuracy of the derivatives by up to two orders of magnitude. The PAD technique’s biggest disadvantage lies in the necessity to compute the iterative map’s Jacobian, which for large problems can be prohibitive. Methods are discussed to alleviate this difficulty.