Compressive　sensing　(CS)　theory　states　that　sparse　signals　can　be　sampled　at　a　sub-Nyquist　rate　without　information　loss.　The　combination　of　CS　and　analog-to-digital　converter　(ADC)　has　demonstrated　an　effective　reduction　in　the　conversion　rate.　However,　the　majority　of　prior　CS　ADCs　have　not　been　successful　in　efficiently　optimizing　the　quantization　process.　This　paper　proposes　the　predictive　quantization　method　for　the　CS　successive　approximation　register　ADC.　This　approach　not　only　reduces　the　conversion　rate　but　also　decreases　the　number　of　conversion　bits.　The　pseudo-random　sequence　used　in　random　demodulation,　along　with　the　previous　value,　serves　as　the　basis　for　prediction　to　address　the　challenge　that　results　from　the　randomness　by　mixing.　With　predictive　quantization,　the　reduction　in　the　number　of　bits　per　conversion　contributes　to　improving　overall　power　saving.　The　prototype　circuit　is　designed　in　a　0.18-mu　m　CMOS　process.　The　simulation　results　indicate　that　the　proposed　ADC　successfully　reduces　the　average　number　of　conversion　bits　to　6.97　bits　for　ECG　signals　when　the　resolution　of　ADC　is　10　bits.　There　is　approximately　a　30%　drop　in　the　number　of　conversion　bits.