Aim: This study aimed to evaluate the role of magnetic resonance imaging (MRI) in diagnosing, characterizing, and risk stratifying non-ischemic dilated cardiomyopathy (NIDCM) by assessing ventricular function, myocardial fibrosis, and tissue characteristics. Materials and Methods: A prospective analysis was conducted on 110 patients diagnosed with NIDCM based on left ventricular (LV) dilation and systolic dysfunction (LVEF <45%) without significant coronary artery disease (CAD). Exclusion criteria included significant CAD, contraindications to MRI, and secondary causes of cardiomyopathy. Cardiac MRI was performed using standardized protocols, including cine imaging, T1/T2-weighted imaging, late gadolinium enhancement (LGE), and parametric mapping. Results: The study population included predominantly male (70%) patients with a mean age of 48–51 years. Functional impairment (NYHA Class III/IV) was significantly higher in severe cases (70%, p = 0.022). LVEF and RVEF were uniformly reduced across groups, indicating severe systolic dysfunction, while LV mass and end-diastolic volumes showed a trend of progression with disease severity. LGE analysis revealed comparable fibrosis extent across groups (~25%), but fibrosis mass was significantly higher in severe cases (21.7 ± 7.8 g, p = 0.045). Parametric mapping demonstrated significantly elevated extracellular volume (ECV) in severe cases (30.2 ± 4.3%, p = 0.041) and an increased edema index (2.3 ± 0.7, p = 0.031), highlighting the roles of diffuse fibrosis and inflammation. Biomarkers such as NT-proBNP and troponin did not significantly differ across groups, whereas creatinine levels were elevated in severe cases (1.2 ± 0.3 mg/dL, p = 0.045). Regression analysis identified no significant predictors of LVEF, underscoring the multifactorial nature of systolic dysfunction in NIDCM. Conclusion: MRI is a critical tool in diagnosing and managing NIDCM, offering comprehensive insights into structural, functional, and tissue-level abnormalities. The study highlights the significance of fibrosis and inflammation in disease progression, emphasizing the utility of advanced imaging techniques like LGE and parametric mapping. MRI's integration into clinical practice enhances personalized treatment strategies, although challenges like accessibility persist.