This research aims to reactivate object-oriented databases using intelligent tools to improve performance and accuracy in modern work environments that require processing large amounts of complex data. The object-oriented database model faces challenges in query speed, result accuracy, and handling tangled or missing data. An integrated framework based on machine learning algorithms and intelligent filtering techniques was designed to enhance query performance. We implemented this framework in a pilot environment using Java and an ObjectDB database and compared performance before and after employing intelligent tools. The results showed a significant reduction in query execution time and an increase in result accuracy, along with improved interpretability and handling of missing data. This research enhances the potential of adopting intelligent tools to improve the performance of object-oriented databases and provide effective and flexible solutions to contemporary data management challenges.
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