Bacterial load and drug resistance pattern associated with some ready-to-eat (RTE) street foods such as Chatpoti, Fuchka, Singara, Panipuri, Ghugni-muri, Chola and water of Dhaka South City Corporation were investigated. Most of the samples were found to be contaminated and the bacterial load ranged from 2.4 × 104 - 9.2 × 106, 1.2 × 103 - 7.3 × 105 and 1.1 × 103 - 1.6 × 106 cfu/g of aerobic heterotrophic, coliform bacteria and Staphylococcus, respectively. The highest coliform load (7.3 × 105 cfu/ml) was found in the water of Gulistan. The highest aerobic heterotrophic bacteria (9.2 × 106 cfu/g) and Staphylococcus (1.6 × 106 cfu/g) were observed in the Chatpoti of Nilkhet. Among the isolated 100 different bacterial colonies, 20 Gram-positive and 8 Gram-negative isolates were studied in details. Based on the morphological and biochemical analysis, the Grampositive isolates were identified as Staphylococcus (9), Bacillus (4), Kurthia (3), Planococcus (1), Micrococcus (1), Listeria (1) and Renibacterium (1). Gram-negative isolates were identified as Klebsiella pneumoniae (3), Yersinia pestis (1), Y. pseudotuberculosis (1), Escherichia coli (1), Enterobacter aerogenes (1) and Plesiomonas shigelloides (1). The multi-drug resistance (MDR) pattern was found to be diverse. Among the MDR bacteria, Enterobacter aerogenes was found to be resistant against six common antibiotics. Plesiomonas shigelloides and Yersinia pestis were found to be resistant against five antibiotics. The multiple antibiotic resistant (MAR) indices of Gram-negative isolates ranged in between 22.22 and 66.67%. Conventionally identified five bacterial isolates with significant MAR indices were further identified with 16S rDNA sequencing and found to be as Enterobacter cloaceae Ecl1, Plesiomonas shigelloides CIFRI, Aeromonas sp. TIL_WAK_4, Aeromonas sp. 280 and Klebsiella pneumoniae KPS77. Conventional identification was found to be accurate for three isolates but the two Yersinia sp. were identified to be as Aeromonas sp. in 16S rDNA sequencing. Dhaka Univ. J. Biol. Sci. 27(1): 27-36, 2018 (January)