Background: Antimicrobial resistance complicates the management of skin and soft tissue infections (SSTIs), particularly in low- and middle-income countries where microbiological surveillance remains limited. We compared the microbiological spectrum and antimicrobial resistance patterns of wound-associated SSTIs between tertiary-care hospitals in Ghana and Germany. Methods: This retrospective bicentric cohort study analysed routine microbiological data from 309 patients in Ghana and 294 patients in Germany. 329 bacterial isolates from Ghana and 816 bacterial isolates from Germany were included. Pathogen distribution, antimicrobial susceptibility, and the prevalence of methicillin-resistant Staphylococcus aureus (MRSA), third-generation cephalosporin-resistant (3GC-R) Enterobacterales, and carbapenem-resistant Gram-negative bacteria were compared descriptively. Results: The microbiological spectrum differed markedly between the two cohorts. Gram-negative bacteria predominated in Ghana (83.9%), whereas Gram-positive organisms predominated in Germany (62.9%). Escherichia coli, Pseudomonas aeruginosa, and Klebsiella spp. were the leading pathogens in Ghana, while Staphylococcus aureus was the predominant pathogen in Germany. Compared with Germany, Ghanaian isolates exhibited substantially higher resistance to third-generation cephalosporins, fluoroquinolones and aminoglycosides. 3GC-R Enterobacterales were identified in 52.8% and 15.6% of evaluable isolates in Ghana and Germany, respectively. Carbapenem resistance among evaluable Gram-negative isolates was detected in 15.2% and 11.2%, respectively. MRSA prevalence (45.2% vs. 4.1%) was also considerably higher in Ghana than in Germany. Conclusions: Wound-associated SSTIs in Ghana and Germany differ substantially in pathogen distribution and antimicrobial resistance profiles. The predominance of Gram-negative pathogens and the high resistance burden observed in the Ghanaian cohort highlight the need for strengthened microbiological surveillance and antimicrobial stewardship. Institution-specific resistance data are essential to optimize empirical antimicrobial therapy across different healthcare settings.