We developed a predictive metric for professional bodybuilding competitions, enabling accurate forecasts of the resulting rankings of competitors. This metric-based ranking serves as an alternative to the traditional alphabetical grouping during competition pre-judging. Bodybuilding competition data is collected using BeautifulSoup from the NPC News Online website. Competitors are assigned a numerical value based on their competition history using the Elo rating model. After each competition, their Elo ratings are adjusted based on the Elo ratings of competitors they outranked and those who outranked them. From the Elo ratings, we can predict the outcomes of upcoming competitions. The results indicate that predicted competition outcomes using Elo ratings significantly outperform alphabetical ordering, suggesting that metric-based ranking is a more effective method for initial competitor grouping.