In error-tolerant applications such as multimedia processing, machine learning, and image filtering, a trade-off between accuracy and performance can enable significant energy and delay savings. Approximate computing offers a powerful design paradigm by intentionally sacrificing computational precision to improve efficiency. This paper presents a class of Hybrid Parallel Prefix Adders (HyPPA) where the Least Significant Bits (LSBs) are computed using approximate adder architectures—such as Lower-part OR Adder (LOA), Copy Adder, and Error-Tolerant Adder Type 1 (ETA-1)—while the Most Significant Bits (MSBs) are computed using accurate parallel prefix adders (PPAs) like Kogge-Stone or Brent-Kung. These hybrid designs are synthesized, implemented, and evaluated using 90nm CMOS technology. Results show up to 57% power reduction, 65% energy savings, and minimal accuracy degradation, making the proposed architectures ideal for energy-efficient and error-resilient digital systems.