Authors : Tarikka B.; Saanvi G.; P. Sri Lekha; Dr. Sivasakti Balan D. P.; R. J. Thayumanaswamy

Volume/Issue : Volume 10 - 2025, Issue 12 - December

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Google Scholar : https://tinyurl.com/3p87h836

Scribd : https://tinyurl.com/5ctnpda5

DOI : https://doi.org/10.38124/ijisrt/25dec1306

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

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Abstract : Bayes' Theorem is a mathematical formula in probability theory that calculates the conditional probability of an event based on prior knowledge of related conditions. Bayes' Theorem is used in many areas like weather forecasting, spam filtering, medical diagnosis, and more. Other examples include credit risk assessment, quality control, search engines, recommendation systems, stock market prediction, and AImachine learning. This research highlights how Bayes theorem helps in interpreting medical test results, classifying emails as spam or legitimate and to identify suspects or causes in Forensics more accurately.

Keywords : Bayes Theorem, Probability, Theoretical Frame, Smoking, Covid 19.

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