Context: The distribution of uropathogens and their susceptibility pattern to antibiotics vary regionally and even in the same region, they change over time. Therefore, the knowledge on the frequency of the causative microorganisms and their susceptibility to various antibiotics are necessary for a better therapeutic outcome. Aim: The aim was to study the frequency and distribution of uropathogens and their resistance pattern to antibiotics in a tertiary care hospital. Settings and Design: Retrospective study for a period of 1 year from January 2011 to December 2011 in a tertiary care hospital. Materials and Methods: The culture and sensitivity data of the uropathogens from suspected cases of UTI were collected from the records of Microbiology Department for study period. Midstream urine samples were processed for microscopy and culture, and the organisms were identified by standard methods. Antibiotic susceptibility was carried out by KirbyâBauer disk diffusion method according to Clinical and Laboratory Standards Institute guidelines. Descriptive statistics were used to analyze the data. Results: Of 896 urine samples, 348 (38.84%) samples were positive for urine culture. Escherichia coli (52.59%) was the most common organism followed by Klebsiella. E. coli was least resistant to imipenem (8%) and amikacin (16%) and was highly resistant to coâtrimoxazole (69%) and ampicillin (86%). Klebsiella species were least resistant to amikacin (26%) and were highly resistant to ampicillin (92%). The overall resistance pattern of antibiotics to uropathogens was the highest to nalidixic acid (79%) followed by coâtrimoxazole (75%) and ampicillin (72%). Good susceptibility was seen with imipenem and cephalosporins. Conclusion: E. coli is still the most common uropathogen. Nalidixic acid, ampicillin, coâtrimoxazole, and firstâgeneration fluoroquinolones have limited value for the treatment of UTI. Sensitivity to imipenem and amikacin are still retained and may be prescribed for complicated UTI. Routine monitoring of drug resistance pattern will help to identify the resistance trends regionally. This will help in the empirical treatment of UTIs to the clinicians.