Purpose: This paper empirically examines the impact of debt structure on the performance of some select Indian automobile firms listed on the National Stock Exchange (NSE) and constituents of Nifty 50 during the seven years from 2016 to 2022.

Methodology: The study used the panel data regression technique and used multiple tests to choose the best model between the alternative models namely Pooled Regression Model (PRM), Fixed Effect Model (FEM), and Random Effect Model (REM). Six automobile companies being part of Nifty 50 listed in NSE were used for the seven years from 2016 to 2022. The data used strongly balanced panel data and relied on test statistics for the significance and reliability of the dataset.

Findings: The diagnostic tests in addition to the Hausman test confirmed FEM as an appropriate model for estimating the impact of debt structure on the performance of sample automobile firms for the first two equations whereas REM is found suitable for estimating the third and fourth regression equations. The results revealed the regression model using ROE and ROA as the dependent variable is the best fit and significant model. The other two regression models using P/E and EV/EBITDA as dependent variables are not significant as the model does not fit the data very well which can be evident from the value of R-squared i.e., only 15% and 8% respectively. The study found debt structure and the firm's size are negatively correlated with ROE on the other hand firm’s size is negatively associated with ROA. Therefore, it can be concluded that debt structure and firm size have a negative effect on the performance of the sample automobile firms i.e., an increase in debt and firm size leads to a decrease in performance and vice versa.

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Keywords: Financial Leverage, Firm Performance, Panel Regression.