Brain metastases (BMs) from bronchopulmonary tumors are a major cause of morbidity and mortality and significantly reduce the quality of life in oncology patients. Their treatment depends on imaging features (size, number, location) and their genetic mutation subtype, small-cell lung cancer (SCLC) or non-small cell lung cancer (NSCLC). In patients with SCLC, prophylactic whole-brain radiotherapy (WBRT) with hippocampal sparing (HS) is recommended, whereas in patients with NSCLC, systemic targeted therapy is preferred. Multiple studies have analyzed the MRI morphology of BMs from both SCLC and NSCLC to identify specific imaging characteristics that can guide the selection of appropriate treatment. However, data on lung cancer (LC) brain metastases in patients from Romania are scarce or nonexistent. Our purpose was to investigate the imaging features of both NSCLC and SCLC BMs in our population using conventional MRI protocols. We selected patients from our hospital between 2019 and 2023 who had a histopathological diagnosis of LC BMs and underwent complete MRI exams prior to any radiotherapy or surgical treatment. For every MRI feature, we created both numerical and categorical variables, which were further studied using univariate, bivariate, and multivariate analyses, as well as a machine learning algorithm. We found 62 patients (49 men, 79.03% and 13 women, 20.96%) with confirmed LC BMs, of which 53 (85.49%) had NSCLC and 7 (11.29%) had SCLC. The sites affected were the cerebral hemisphere (56.46%), the cerebellum (40.32%), and the deep nuclei (6.45%), with the latter affecting relatively younger patients (P = 0.01), most notably in the case of thalamic situs (P = 0.0001). The SCLC subgroup showed a P value of 0.025 for the number of lesions, indicating diffuse spread. The AI algorithm identified positive and negative imaging diagnostic prediction variables, including internal vascularization and the number of lesions, respectively, as well as cystic lesions and internal hemorrhage. Further multicentric studies are needed to unravel the MRI features of LC BMs.