Powered knee and ankle prostheses have the potential to improve the mobility of individuals with a lower limb amputation. As the number of different ambulation modes the prosthesis can be configured for increases, so too does the challenge of how to best transition the prosthesis between these modes. Pattern recognition systems have been suggested as a means to provide seamless and natural transitions, although error rates need to be reduced for these systems to be clinical viable. Delaying mode transitions by a small window may be one way to reduce error rates and improve reliability. The goal of this study was to develop and test a system for powered lower limb prostheses that introduced a delay between mode transitions. Three transfemoral amputees used a knee-ankle prosthesis to stand, walk on level ground, ascend/descend a ramp, and ascend/descend stairs. On Day 1 mode transitions occurred at a gait event (e.g., heel contact), and on Day 2 mode transitions occurred 90 ms following a gait event. A mode-specific pattern recognition system was trained and tested on each day. The 90 ms transition delay did not negatively affect users' performance ambulating with the prosthesis. Offline classification error results showed that the 90 ms delay reduced overall classification errors from 1.30% [0.29%], mean [SD], for the non-delayed system to 0.42% [0.22%] for the delayed system. These results demonstrate that delaying mode transitions by a small window of time can reduce overall errors, which moves these systems one step closer to clinical viability.