Antimicrobial resistance (AMR) poses a growing threat to global health, requiring innovative tools to monitor and predict resistance trends. This article demonstrates how to use PHP and machine learning to predict antimicrobial resistance patterns, leveraging data and predictive models for actionable insights. We’ll walk through a practical example using a function that predicts resistance percentages by year and forecasts trends for the next five years.