This chapter measures technical efficiency scores (TE) of government and government-aided schools for secondary education in Kolkata using primary survey data, collected through multistage stratified random sampling procedure, employing data envelopment analysis and obtains the determinants of such TE. It is evident that about 52% of the sample schools are not perfectly efficient, implying that these schools can produce more output with existing resources, and the magnitude of TE varies among the schools. It is observed that a huge percentage of students undertake private tuition which may affect TE. Thus, to find out the determinants of TE, the paper considers the effect of (i) percentage number of students taking private tuition, (ii) the role of the headmaster/mistress (HM), (iii) the characteristics of the HM, (iv) the characteristics of the teachers, (v) school infrastructure and administration related variables, (vi) school characteristics and student composition-related variables, (vii) policy-related variables, (viii) socio-economic background of the students, (ix) quality of school attributes based on student’s perceptions. The results support that the TE is positively related to the percentage number of students taking private tuition and the part of the variation of TE which is not explained by the percentage number of students taking private tuition is low; it ranges from 1.5 to 23.8%, with mean value 8.28%. Further, TE is negatively and significantly related to service experience of headmaster/mistress (HM) and full time teachers, meaning that schools with relatively junior HM and junior teachers will have higher TE. TE is positively related to (a) the role of the HM in school management, i.e., while taking any policy decision whether HM interacts with students and teachers, and also the interaction between this variable with the variable specifying the frequency of interaction of HM with State Education Department; the existence of interaction term implies, given the value of one variable, TE will in turn depend on the value of the other, showing the importance of the both, (b) school infrastructure variables, i.e., whether Librarian of the school is on duty, (c) policy variable like (i) the proportion of students getting Kanyashree (an initiative taken by the government of West Bengal to improve the life and status of girls by helping economically backward families with cash transfer so that they do not arrange for the marriage of the girls before eighteen years), where nonlinear inverted U-shaped relationship between the proportion of students getting Kanyashree and TE is obtained, with positive marginal effect for the present sample, implying that an increase in Kanyashree will boost up TE and (ii) on the availability of government fund to the schools, (d) the school characteristics, student composition, and students characteristics-related variables like the class size as represented by the number of sections in the class, the proportion of reserved category students, and the proportion of students having text book at their home.KeywordsEfficiency analysis of secondary educationGovernment and government-aided schoolsData envelopment analysisPrimary survey dataKolkataIndia