In　conditioning　air　load　prediction　model　based　on　SVR　model,　the　Simulated　Annealing　(SA)　has　been　provided　in　order　to　surmount　the　disadvantage　that　the　SVR　model　selects　learning　parameters　depending　on　experience.　The　Modified　Simulated　Annealing　(MSA)　has　been　proposed　to　optimize　the　SVR　prediction　model,　in　which　the　annealing　plan　and　disturbance　range　has　been　improved.　Case　researches　in　the　paper　show　that　MSA　algorithm　is　of　strong　global　optimization　capability,　good　robustness　and　short　calculation　consumption.　Compared　with　SA-SVR　model　and　the　VFSA-SVR　model,　MSA-SVR　air　conditioning　load　prediction　model,　the　results　show　SVR　model　parameters　obtained　through　MSA　optimization　can　effectively　improve　the　predication　accuracy　and　stability　of　the　air　conditioning　load　prediction.