Methodology

Bloomberg Businessweek’s Best B-Schools relies on graduating students, recent alumni and companies that recruit MBAs to assess and comment on the programs ranked. Their answers to questions about everything from jobs to salaries, classroom learning to alumni networks, form the heart of this ranking. These stakeholders can have differing and overlapping interests. As such, we rank schools based on five indexes: compensation, learning, networking, entrepreneurship and inclusion (for US schools only). Our methodology consists of two steps.

Generating weightings for each index.

Survey responses determine the relative weighting of the indexes. All three stakeholder groups are asked to rank the five most important factors when considering business school (or, in the case of employers, the most sought-after qualities in business school graduates).

Respondents have nine to 13 options to choose from. Each factor is tied to one of the five indexes. Stakeholders’ answers determine the weighting of each index. Five points are awarded for each top-ranked factor, four points for the second-ranked answer, and so on. Totals are adjusted in two stages:

• We adjust point totals according to which stakeholder group the respondent belongs to:

• We adjust point totals to account for the fact that not all indexes are equally represented in the factor choices.

This year’s surveys resulted in the following index weightings:

(Figures do not total 100% because of rounding.)

Determining school scores for each index.

Survey takers first answer how well their schools delivered on the five factors chosen in the previous section based on a seven-point scale (“completely agree” receiving seven points and “completely disagree” receiving one point). Next, they’re asked to agree or disagree with statements regarding their business school experience that appear for all respondents, regardless of which factors they chose initially. These statements are also tied to one of the five indexes and are scored on the same seven-point scale; they touch on the following themes:

Learning: For the schools’ core mission, we explore the quality, depth and range of instruction, focusing on the curriculum relative to real-world business situations, with emphasis on: innovation, problem-solving, and strategic thinking; mentoring and support from instructors; class size; and collaboration.

Networking: This gauges the quality of networks cultivated by classmates; students’ interactions with alumni; effectiveness of the career services office; quality and breadth of alumni-to-alumni engagement; and recruiters’ assessment of the school’s brand power.

Entrepreneurship: Students and alumni tell us whether their school took entrepreneurship as seriously as other career paths and rate the quality of training they received to start a business. Recruiters rate schools according to whether graduates show exceptional entrepreneurial skills and drive.

As the table below shows, these survey questions account for the entirety of each school’s raw score on the Learning, Networking and Entrepreneurship indexes. Point totals are adjusted according to the first table above. The Compensation Index has additional components; the Inclusion Index score is based on demographics of the first-year class:

Compensation Index

In addition to survey questions regarding compensation, we also collect MBA Career Services & Employer Alliance (MBA CSEA) employment and compensation data from schools. These figures, outlined in the table above, collectively account for 52.5% of a school’s Compensation Index score.

For each of these variables, the school with the minimum figure among all schools is given one point while the school with the maximum figure is given seven points. All other schools are scored proportionally between these two extremes. The following diagram illustrates an example for assigning scores to the “salary after graduation” component:

For non-US schools, salaries submitted in local currencies are converted to US dollars, using the average exchange rate for the year ended June 30, 2025. Salaries aren’t adjusted for parity in purchasing power.

The 1-7 raw scores from the survey questions and the compensation data are then weighted 47.5% and 52.5%, respectively, for a final raw score for the Compensation Index.

Inclusion Index

From US schools, we also collect data on the race, ethnicity and gender of their class members. The Inclusion Index rewards schools for recruiting both minority students and women and nonbinary students, with additional weight given to underrepresented minorities. It is calculated as follows:

Race and Ethnicity (50%)

Total minority population

Schools provide us with percentages of the first-year class of American students for the following groups: White, Black, Asian, American Indian, Hawaiian/Pacific Islander, and Hispanic (of any race). These groups are categorized as such by the schools when submitting data to the federal government.

Before summing up the minority percentages, we adjust each group’s figure according to the “GMAT pipeline.” A multiplier is used to adjust a school’s minority group population based on that group’s presence in the GMAT test-taking population relative to the US population. By comparing the GMAT makeup and the US population makeup, we are able to identify overrepresented minority groups such as Asian students (GMAT % greater than US %) and such underrepresented minority groups as Black and Hispanic students (GMAT % less than US %). We then give schools more credit for the underrepresented minority students they recruit.

That multiplier is then applied to each group’s true percentage. For example, a school with 20% Black students would have an “adjusted Black share” of (20*1.83) = 36.6%. Below are the multipliers.

Students can identify as more than one race and/or ethnicity. Because of this, when including White students, the total summed population of all racial/ethnic groups can exceed 100%. Similarly, if the identities of some students are unknown, the summed total can be less than 100%. To treat schools equally, a normalizing factor is introduced to assume all schools’ totals equate to 100%. For example, if a school’s summed total of all groups equals 115%, while another’s equals 90%, the former’s figures will each be adjusted down by a factor of (100/115 = 0.87), while the latter’s figures will be adjusted upward by (100/90 = 1.11).

We sum up all adjusted racial/ethnic shares of all minority groups for each school and multiply it by that school’s normalizing factor to obtain a total adjusted percentage of minority students.

To reduce the impact of outliers, we next take the logarithm of each total percentage score. The transformed scores are normalized onto a 1-100 scale. Schools that do not provide race and ethnicity data receive a zero.

Gender (50%)

Total women + nonbinary population

We calculate the total percentages of women and nonbinary students for each school.

We then take the logarithm of each total percentage score to reduce the impact of outliers. The transformed scores are then normalized onto a 1-100 scale. Schools that do not provide gender data receive a zero.

Final Scoring

For the final inclusion score, log-adjusted scores for race/ethnicity and gender are averaged for schools that supplied this data, then rescaled from 1-7 for a final number (7 would be awarded to a theoretical school with the maximum minority and women/nonbinary populations of all schools in the ranking; 1 represents a school with the lowest percentages of both minority and women/nonbinary enrollment). This figure is used when applying the Inclusion Index’s weighting to a school’s overall score for the entire ranking. Schools with fewer than 10 US students are excluded from the Inclusion Index. In these cases, the index’s weight is redistributed proportionally across the other four indexes.

Final Overall Score

Following the above calculations, schools that provided data have raw scores between 1 and 7 for each index. Schools providing no inclusion data received a 0 for that index. These index scores are then rescaled from 0 to 100. A raw score of 7 equates to 100, while a raw score of 1 is represented by 0. A school’s raw score for each index is calculated proportionally between these two extremes.

These 0-100 scores are then weighted according to the index weights outlined in Step 1 for a final overall score and ranking.

Regional Results

We display regional pages for EMEA, APAC and Canada in addition to one for the US. We scored schools in two separate groups, US and non-US, on a 0-100 scale.

Other Features

Ranking Personalization

To help readers customize their use of the tool and explore the schools more broadly, we created filtering tools enabling readers to sort schools by a range of salaries, geographic preferences and industry choices.

Campus Atmosphere

We asked broad questions to describe what campus life is like for female, LGBTQ and minority students, such as whether “women are given equal opportunity to participate in class discussions and on teams” and whether “minorities are well represented among the faculty and administration.” We also focused on questions about the B-school curriculum, such as whether “minority protagonists are well represented in case studies.”

Quotes Highlighting What’s Best About a School

“What is the best thing about your MBA program?” We received 6,382 responses from students and alumni. We used natural language processing to identify representative comments from each school based on their common themes and keywords. We eliminated duplicates.

Key Numbers

The Universe

Bloomberg ranked 102 business schools around the world. Programs can be based in any country, but MBA classes must be taught primarily in English.

All schools were required to submit employment data for the Class of 2024, following standards set by MBA CSEA, a trade group founded in 1994 to establish and collect consistent, comparable, peer-reviewed data.

Schools were then given surveys to distribute to three stakeholder groups:

• Students who graduated from Oct. 1, 2024, through Sept. 30, 2025
• Alumni who graduated from Oct. 1, 2016, through Sept. 30, 2019
• Employers who recruited MBA graduates for full-time positions between 2022 and 2024

With the help of the business schools, we surveyed 5,372 students, 9,143 alumni and 766 employers.

Schools must abide by Bloomberg’s strict code of ethics, which is meant to ensure that all survey respondents voluntarily take part in our surveys with no bias or pressure from school officials or their peers.

Minimum thresholds for survey response rates are based on the size of a school’s graduating and alumni classes. Schools that did not meet survey thresholds were eliminated. We qualified two schools that met participation requirements for two of the three stakeholders, but were just shy of the stated threshold for the third group of surveys.

All ranked schools confirmed the accuracy of their submitted data in August and September.