Choosing the optimal capital structure is one of the problems that have been discussed since the middle of last century in terms of dependence on equity or debt. Many theories and opinions were put forward on this subject in several directions with many variables and considered the composition of capital effective on the performance of companies with results differing from one scholar to another. Based on the importance of the industrial sector at the global level and the characteristics of this sector in terms of the need to invest large amounts in fixed capital, it is interesting to study the capital structure of the industrial companies and its impact on their performance, as well as the impact of long-term loans and financial leverage on the financial performanceof industrial companies. Many researches were conducted on the industrial sector outside the Swedish market. The purpose of this study is to investigate and present an analysis of the possible correlation between the capital structure and the performance of companies in the Swedish industrial sector.The statistical analysis shows that all debts have a significant negative relationship with profitability. This came compatible with the pecking-order theory, where if the industrial companies use internal financing, the Corporate performance will be better, and the profit rates will behigher.This study includes about 68% of Swedish industrial companies listed in Nasdaq Stockholm and has quarterly data published during the study period 2010 -2018. To ensure access to the results, the sample was limited to companies with debts in their financial statements. The study is limited to commenting on the return on invested capital, the return on assets and the return on equity, which were deemed dependent variables, and examines the impact of long-term debt, short-term debt, financial leverage and debt on the above dependent variables. With panel data coming from series and cross-sectional quantitative studies, this paper investigates the Swedish industrial companies. Empirical data was collected from quarterly reports covering a nine-year period (2010-2018). Afterward, statistical testing was performed.