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SCI."],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>Employee attrition refers to the phenomenon of employees leaving an organization. High attrition rates can have a profoundly adverse impact on organizations, resulting in the loss of talent, reduced productivity, increased recruitment costs, and a negative effect on employee morale and confidence. This paper presents a novel model for predicting employee attrition by leveraging the synergistic combination of the Stacked Classifier model and Explainable AI techniques. By combining diverse machine learning algorithms into an ensemble model and leveraging XAI methods, this study not only forecasts attrition with precision but also explains the underlying decision-making process, making the predictions interpretable and actionable. The proposed model yields an accuracy of 98.8%, a precision of 98.1%, and an F1-score of 98.5%. 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