Predicting the 2026 Oscars: Unveiling Insights Through Machine Learning
Harnessing Data to Forecast Academy Award Winners
Predicting the 2026 Oscars: A Machine Learning Approach
Every year, the Academy Awards captivate audiences worldwide, celebrating the best achievements in filmmaking. However, predicting the winners remains a challenge—even for industry insiders. Awards season involves complex dynamics: critical acclaim, festival momentum, guild awards, box office performance, and sometimes pure narrative momentum.
At BigML, we like to approach the problem from a different perspective: using machine learning.
Using historical data from previous Academy Awards along with key indicators from the current awards season, we trained models to estimate the probability of each nominee winning their category. By learning patterns from past Oscar events, our machine learning models can detect trends that often precede a victory. In this post, we present our predictions for the 2026 Oscars (the 98th Academy Awards).
Data and Methodology
To build our predictive models, we collected structured data for nominees across major Oscar categories. Our dataset includes 1,427 movies nominated for various awards from 2001 to 2026 and 299 features for each movie, such as:
- Nominations and wins from precursor awards (Golden Globes, BAFTA, SAG, Critics’ Choice, etc.)
- Total nominations received by the film
- Historical performance of the director or actors
- Film release timing and festival reception
- Genre and production characteristics
These features trained classification models capable of predicting the likelihood of a nominee winning the Oscar. Once trained using data from previous Academy Awards ceremonies, we applied our models to the 2026 nominees to estimate their probabilities of winning.
The 2026 Predictions
Best Picture
The Best Picture category is often the most complex to predict. Factors like industry momentum, ensemble recognition, and the overarching narrative surrounding the film play crucial roles.
Among this year’s contenders, One Battle After Another, directed by Paul Thomas Anderson, has emerged as a strong frontrunner. The film has accumulated several major precursor awards, giving it a robust statistical profile.
Another major contender is Sinners, directed by Ryan Coogler, which leads the nominations tally with 16 nominations and has strong support across multiple categories. Other notable nominees include Hamnet, Frankenstein, and Avatar: Fire and Ash, each with varying levels of awards-season momentum.
Predicted Winners
- Best Picture: One Battle After Another
- Best Director: Paul Thomas Anderson
- Best Actress: Jessie Buckley
- Best Actor: Timothée Chalamet
- Best Supporting Actress: Amy Madigan
- Best Supporting Actor: Benicio Del Toro
- Best Original Screenplay: Sinners
- Best Adapted Screenplay: One Battle After Another
Technical Categories
Our predictions also extend to more technical categories:
- Best Cinematography: Sinners
- Best Costume Design: Frankenstein
- Best Film Editing: One Battle After Another
- Best Sound: F1: The Movie
- Best Visual Effects: Avatar: Fire and Ash
- Best Makeup and Hairstyling: Frankenstein (with Sinners close behind)
- Best Music, Original Song: Sinners (tied closely with KPop Demon Hunters and Train Dreams)
- Best Music, Original Score: Sinners
- Best Production Design: One Battle After Another (with Sinners a close second)
- Best International Feature Film: The Secret Agent
- Best Animated Feature Film: KPop Demon Hunters
Final Thoughts
Predicting the Oscars is always a challenge. Even the most sophisticated models cannot fully capture the human factors that influence Academy voters—personal taste, industry narratives, and cultural context. Nevertheless, machine learning offers a powerful means to analyze historical patterns and quantify signals that often precede Oscar victories.
Will the Academy follow the data this year? Or will there be surprises? We’ll find out when the winners are announced at the 98th Academy Awards. Good luck to all the nominees!