Taylor-series integration is a numerical integration technique that computes the Taylor series of state variables using recurrence relations and uses this series to propagate the state in time. A Taylor-series integration reentry integrator is developed and compared with the fifth-order Runge–Kutta–Fehlberg integrator to determine whether Taylor-series integration is faster than traditional integration methods for reentry applications. By comparing the central processing unit times of the integrators, Taylor-series integration is indeed found to be faster for integration without wind and slower with wind, unless the error tolerance is 10−8 or lower. Furthermore, it is found that reducing step sizes to prevent integration over discontinuities is not only needed for Taylor-series integration to obtain maximum accuracy but also for Runge–Kutta–Fehlberg methods. In that case, the Runge–Kutta–Fehlberg integrator does become several times slower than Taylor-series integration.