Abstract: In this paper, the ozone pollution sensitive meteorological conditions are analyzed by using wind speed, wind direction, air temperature, precipitation, relative humidity and ozone concentration data from 2015 to 2017. Meanwhile, the ozone pollution meteorological conditions index (OPMCI) has been designed based on probability statistics and correlation analysis. First, based on the contribution of various meteorological factors to the formation of ozone, the OPMCI values them comprehensively.Second, as the correlation between temperature and ozone pollution is the largest, temperature is selected as the basis factor.The joint contribution score of temperature and other meteorological factors minus temperature basis score is the score of each meteorological factor at different grades. Third, according to the historical data, the ozone exceeding standard rate and average ozone concentration at different grades are obviously different, so the OPMCI conforms to the observation and runs well in Shenzhen.