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Machine Learning-Based Financial Performance Prediction of Indian Pharmaceutical Companies Using Financial Leverage Indicators


Authors : N. Naveen Kumar; Dr. Umadevi Ramamoorthy

Volume/Issue : Volume 11 - 2026, Issue 8 - August


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

DOI : https://doi.org/10.38124/ijisrt/26aug698

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


Abstract : The financial results and long-term viability of corporate organisations are Financial leverage has a major impact. This research looks at The impact of financial leverage on the financial performance of a few Indian listed pharmaceutical businesses between 2021 and 2024. The annual reports and audited financial statements of particular pharmaceutical businesses were used to gather secondary data. While Financial performance is evaluated using Return on Assets (ROA), Return on Equity (ROE), Earnings per Share (EPS), and Return on Capital Employed (ROCE), financial leverage is quantified using metrics like the Debt-to-Equity Ratio (DER), Debt Ratio (DR), and Interest Coverage Ratio (ICR). To look into the connection between financial success and financial 111 leverage and to create predictive models, the gathered data is pre processed and analysed using Pearson Correlation Analysis, Multiple Random Forest Regression, Decision Tree Regression, Linear Regression,, and K-Means Clustering. R2 Mean Absolute 222 Error (MAE), score Mean Squared Error (MSE), and 666 333 utilize Root Mean Squared Error (RMSE) to evaluate the prediction models' performance.

Keywords : Financial Leverage, Financial Performance, Machine Learning, Multiple Random Forest, Decision Tree, and Linear 44 Regression Pearson Correlation, K-Means Clustering, Pharmaceutical Companies, India.

References :

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The financial results and long-term viability of corporate organisations are Financial leverage has a major impact. This research looks at The impact of financial leverage on the financial performance of a few Indian listed pharmaceutical businesses between 2021 and 2024. The annual reports and audited financial statements of particular pharmaceutical businesses were used to gather secondary data. While Financial performance is evaluated using Return on Assets (ROA), Return on Equity (ROE), Earnings per Share (EPS), and Return on Capital Employed (ROCE), financial leverage is quantified using metrics like the Debt-to-Equity Ratio (DER), Debt Ratio (DR), and Interest Coverage Ratio (ICR). To look into the connection between financial success and financial 111 leverage and to create predictive models, the gathered data is pre processed and analysed using Pearson Correlation Analysis, Multiple Random Forest Regression, Decision Tree Regression, Linear Regression,, and K-Means Clustering. R2 Mean Absolute 222 Error (MAE), score Mean Squared Error (MSE), and 666 333 utilize Root Mean Squared Error (RMSE) to evaluate the prediction models' performance.

Keywords : Financial Leverage, Financial Performance, Machine Learning, Multiple Random Forest, Decision Tree, and Linear 44 Regression Pearson Correlation, K-Means Clustering, Pharmaceutical Companies, India.

Paper Submission Last Date
31 - October - 2026

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