Purpose: The purpose of this study was to construct prediction model for winning and losing of baseball games, and also differentiate the key factors of winning and losing. Method: The research area would mainly focus on Chinese Professional Baseball League (CPBL) and the eighteenth year scoreboard, using content analysis and Delphi research methods and building the factors that influenced the winning and losing of CPBL game. The statistics of logistic regression was used in the analysis in order to construct CPBL prediction model. Results: The results indicated that: 1. According to the expert opinions in this study, key factors which influenced the winning and losing of the game included 22 offensive items, 32 pitching items, and 7 defensive items. 2. Among the attribute factors of offensive, scoring had the highest explanation power which followed by runs, at bats, runner batted in, errors, and squeeze play (p<.05). According to the odds ratio analysis, it discovered that the odds ratio of at bats and errors were less than 1, which meant they were negative factors, and the least was the errors factor (odds ratio=.577). Odds ratio of runs, runner batted in, and squeeze play were larger than 1, which meant that they were positive factors. 3. Among the attribution factors of pitching, game had the highest explanation power which followed by inning pitched, hit batsmen, hits, base balled/walk, and earned runs (p<.05). According to the odds ratio analysis, it discovered that the odds ratio of hit batsmen and earned runs were less than 1, which meant that they were negative factors. Odds ratio of inning pitched, hits, and base balled/walk were larger than 1, which meant that they were positive factors. Conclusion: Based on the findings, hitting and batting predictive items would be a good reference for prediction of winning and losing, and also for team management to increase competitive ability.