The meta-QTL analysis was performed to identify the most effective and stable QTLs related to quantitative traits in peach (Prunus persica). In the present study, a QTL database containing information of molecular markers in different peach populations was constructed. Then, a new genetic consensus map based on the Kosambi map function was created. A number of 137 QTLs from the initial pool were projected in the constructed genetic consensus map and eventually 22 meta-QTLs (MQTLs) on different linkage groups of the peach genome was detected. The linkage group 4 (LG4) had the highest number of MQTLs for the assessed traits. According to co-localization frequency analysis between existing QTLs in the detected MQTLs regions, blooming time had the highest co-localization (67%) with the QTLs of fruit weight. Pleiotropy or strong linkage between genes controlling blooming time and fruit weight could be explained for the co-localization of the tested traits. The MQTL.LG4.3 and MQTL.LG4.2 containing 14 and 10 QTLs in original genomic regions were identified as the most stable and reliable MQTLs controlling most of the traits tested in peach.