Read the result, then trace it back to the races and sources. Each state has its calculation card: hover over the map, search a name or pick a state.
One race. Its numbers. Its calculation. Hover, tap or search for a state.
1059 seats. Lula’s coalition : 256.3 (186–336) · Flávio Bolsonaro’s PL : 145.7 (86–220).
| List | Expected seats | 90% | 2022 | Largest party |
|---|---|---|---|---|
| União Progressista | 192.3 | 120–281 | 185 | 55% |
| PT federation | 158.1 | 94–236 | 155 | 24% |
| PL | 145.7 | 86–220 | 126 | 16% |
| MDB | 114.2 | 68–169 | 94 | 3% |
| PSD | 91.6 | 51–143 | 79 | 1% |
| Republicanos | 88.6 | 49–139 | 76 | 1% |
| Podemos | 49.8 | 26–81 | 48 | |
| PSDB-Cidadania | 47.9 | 25–78 | 74 | |
| PSB | 45.9 | 24–74 | 55 | |
| Renovação Solidária | 37.1 | 18–62 | 54 | |
| PSOL-Rede | 27.0 | 12–47 | 29 | |
| PDT | 25.4 | 12–43 | 44 | |
| Avante | 15.5 | 7–28 | 14 | |
| Novo | 9.8 | 3–20 | 5 | |
| Mobiliza | 5.6 | 1–11 | 6 | |
| Agir | 3.9 | 1–8 | 5 |
| State | Leading | Second | Seats |
|---|---|---|---|
| RN Rio Grande do Norte | PT federation 26.8% | PL 26.6% | 24 |
| MT Mato Grosso | MDB 18.0% | Podemos 17.7% | 24 |
| GO Goiás | MDB 16.4% | União Progressista 15.7% | 41 |
| SP São Paulo | PL 18.0% | PT federation 17.3% | 94 |
| ES Espírito Santo | União Progressista 14.5% | Republicanos 13.5% | 30 |
| DF Federal District | União Progressista 15.1% | PL 13.9% | 24 |
| MS Mato Grosso do Sul | União Progressista 22.4% | PL 21.1% | 24 |
| RO Rondônia | União Progressista 16.5% | Renovação Solidária 15.2% | 24 |
| TO Tocantins | União Progressista 18.8% | Republicanos 16.8% | 24 |
| RS Rio Grande do Sul | PT federation 18.5% | União Progressista 16.4% | 55 |
Compared with the largest party by seats in 2022. 11 of 27.
| State | 2022 | Leading in 2026 | Seats | |
|---|---|---|---|---|
| RN Rio Grande do Norte | PSDB-Cidadania 10 | PT federation 26.8% | 6 | |
| MT Mato Grosso | União Progressista 5 | MDB 18.0% | 4 | |
| GO Goiás | União Progressista 9 | MDB 16.4% | 7 | |
| ES Espírito Santo | PL 5 | União Progressista 14.5% | 5 | |
| DF Federal District | PL 4 | União Progressista 15.1% | 4 | |
| MS Mato Grosso do Sul | PSDB-Cidadania 7 | União Progressista 22.4% | 6 | |
| TO Tocantins | Republicanos 7 | União Progressista 18.8% | 4 | |
| AP Amapá | Renovação Solidária 4 | União Progressista 19.0% | 5 | |
| CE Ceará | PDT 13 | PT federation 20.5% | 9 | |
| MA Maranhão | PSB 11 | MDB 22.7% | 9 | |
| PB Paraíba | Republicanos 8 | União Progressista 35.1% | 13 |
| State | Leading list | Second list | Vote gap | Seats | Rating | 2022 |
|---|---|---|---|---|---|---|
| Acre | União Progressista 8 | PDT 3 | 17.6 pts | 24 | Safe | União Progressista 5 |
| Alagoas | MDB 15 | União Progressista 6 | 31.1 pts | 27 | Safe | MDB 14 |
| Amazonas | União Progressista 7 | Avante 3 | 11.0 pts | 24 | Likely | União Progressista 6 |
| Amapá | União Progressista 5 | PDT 4 | 3.5 pts | 24 | Leans | Renovação Solidária 4 |
| Bahia | PT federation 17 | União Progressista 12 | 7.0 pts | 63 | Likely | PT federation 17 |
| Ceará | PT federation 9 | PSB 8 | 3.6 pts | 46 | Leans | PDT 13 |
| Federal District | União Progressista 4 | PL 4 | 1.2 pts | 24 | Toss-up | PL 4 |
| Espírito Santo | União Progressista 5 | Republicanos 4 | 1.1 pts | 30 | Toss-up | PL 5 |
| Goiás | MDB 7 | União Progressista 7 | 0.7 pts | 41 | Toss-up | União Progressista 9 |
| Maranhão | MDB 9 | PL 6 | 7.2 pts | 42 | Likely | PSB 11 |
| Minas Gerais | PT federation 14 | PL 10 | 4.1 pts | 77 | Leans | PT federation 17 |
| Mato Grosso do Sul | União Progressista 6 | PL 5 | 1.2 pts | 24 | Toss-up | PSDB-Cidadania 7 |
| Mato Grosso | MDB 4 | Podemos 4 | 0.2 pts | 24 | Toss-up | União Progressista 5 |
| Pará | MDB 13 | União Progressista 6 | 16.8 pts | 41 | Safe | MDB 13 |
| Paraíba | União Progressista 13 | Republicanos 7 | 15.4 pts | 36 | Safe | Republicanos 8 |
| Pernambuco | União Progressista 12 | PSB 9 | 4.9 pts | 49 | Leans | União Progressista 13 |
| Piauí | PT federation 12 | MDB 10 | 6.5 pts | 30 | Likely | PT federation 12 |
| Paraná | PSD 15 | PL 9 | 11.0 pts | 54 | Likely | PSD 16 |
| Rio de Janeiro | PL 16 | União Progressista 10 | 8.2 pts | 70 | Likely | PL 17 |
| Rio Grande do Norte | PT federation 6 | PL 6 | 0.2 pts | 24 | Toss-up | PSDB-Cidadania 10 |
| Rondônia | União Progressista 4 | Renovação Solidária 4 | 1.3 pts | 24 | Toss-up | União Progressista 6 |
| Roraima | União Progressista 8 | Republicanos 4 | 13.9 pts | 24 | Safe | União Progressista 6 |
| Rio Grande do Sul | PT federation 10 | União Progressista 9 | 2.1 pts | 55 | Toss-up | PT federation 12 |
| Santa Catarina | PL 10 | União Progressista 5 | 11.6 pts | 40 | Likely | PL 11 |
| Sergipe | União Progressista 7 | PSD 4 | 11.4 pts | 24 | Likely | União Progressista 6 |
| São Paulo | PL 16 | PT federation 16 | 0.8 pts | 94 | Toss-up | PL 19 |
| Tocantins | União Progressista 4 | Republicanos 4 | 2.1 pts | 24 | Toss-up | Republicanos 7 |
A predictive model is not one more poll. A poll interviews a sample and describes opinion at a given moment. A model interviews no one. It gathers what can be measured, published surveys, past election results and the electoral rules, and derives from them a distribution of possible outcomes, with their probability. It does not say a party will win so many seats. It says within which range it will finish, and what each candidate’s chances of election are.
Two pollsters published on the same day can differ by several points. The model aggregates every survey published in each state and registered with the Superior Electoral Court, taking into account their age, their size and the pollsters’ reliability.
Polls get it wrong, sometimes badly. The model builds in the size of the errors seen in past elections, without assuming in advance that one side will be underestimated. That is what gives each candidate their chances, and each list its range.
Brazil elects its deputies by proportional representation, state by state, under a complex allocation rule. The model starts from the last election’s results and the make-up of the 2026 lists, then applies the official rule. Tested on the 2022 votes, it recovers 1542 of the 1572 seats actually allocated.
The October 4 elections are not independent. The vote for lists close to the two leading presidential candidates moves with the presidential vote, and the model takes this into account.
A single forecast would give a false sense of certainty. The model therefore replays each race twenty thousand times, varying what is genuinely uncertain. The probability shown is the share of simulations in which the event occurs.
Uncertainty is this model’s product, never its flaw. The simulations are reproducible, and the forecast on the eve of the vote is frozen, then compared with the official results.
Election results and candidacies: Superior Electoral Court. 2026 polls: surveys published by pollsters and registered with the Superior Electoral Court.
Export assemblees_2026_par_etat.csv ↗ · Export the forecasts as JSON ↗
All rights belong to Le Millénaire SAS, 47 rue de Vivienne, 75002 Paris.
Model designed by
Project director: William Thay
Deputy project director: Pierre Clairé
Political analysis and data: Matthieu Hocque
Data analysis, mathematics and validation: Florian Gérard-Mercier