Forecast - Brazil 2026 general elections: Chamber of Deputies

SummaryChamber of DeputiesFederal SenateGovernorsState legislaturesPresidential
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União Progressista favored for first place, no majority in sight
Le Millénaire · 20 000 simulations · updated October 2, 2026 · first round on October 4, 2026
Polls through 2026-10-01 · election in 2 days
The balance of power on October 4
106.3
União Progressista · expected seats
90% : 64–156 · largest 56%
88.3
PL · expected seats
90% : 50–135 · largest 27%
75.0
PT federation · expected seats
90% : 40–118 · largest 15%

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.

The 27 federal units, in three views

One race. Its numbers. Its calculation. Hover, tap or search for a state.

Balance of power

513 seats. Lula’s coalition : 116.1 (77–162) · Flávio Bolsonaro’s PL : 88.3 (50–135).

ListExpected seats90%2022Largest party
União Progressista106.364–15610456%
PL88.350–1359827%
PT federation75.040–1188215%
Republicanos50.425–82402%
PSD43.121–7142
MDB36.517–6041
Podemos30.113–5220
PSB16.67–3015
PSDB-Cidadania16.47–3018
PSOL-Rede16.37–2815
Renovação Solidária14.15–2712
PDT8.33–1616
Avante6.12–127
Novo4.71–103
Missão0.90–20

The seat distribution

04080120160200240

States where first place is within 3 points

StateLeadingSecondSeats
DF Federal DistrictPL 17.6%Republicanos 17.2%8
BA BahiaUnião Progressista 20.6%PT federation 19.5%39
MA MaranhãoPL 18.1%União Progressista 16.6%18
AP AmapáUnião Progressista 19.1%PDT 17.0%8

States where the leading list would change

Compared with the largest party by seats in 2022. 10 of 27.

State2022Leading in 2026Seats
DF Federal DistrictPT federation 2PL 17.6%1
BA BahiaPT federation 10União Progressista 20.6%8
AP AmapáPDT 2União Progressista 19.1%2
PB ParaíbaUnião Progressista 3Republicanos 24.5%3
AM AmazonasPSD 2Republicanos 24.3%3
TO TocantinsRepublicanos 3União Progressista 30.5%3
ES Espírito SantoRepublicanos 2União Progressista 23.0%3
MS Mato Grosso do SulPSDB-Cidadania 3União Progressista 29.5%3
RR RoraimaRepublicanos 3União Progressista 31.3%3
RN Rio Grande do NortePL 4União Progressista 38.7%4

All races

StateLeading listSecond listVote gapSeatsRating2022
AcreUnião Progressista 5MDB 221.9 pts8SafeUnião Progressista 6
AlagoasUnião Progressista 5MDB 227.6 pts9SafeUnião Progressista 5
AmazonasRepublicanos 3PSD 26.4 pts8LikelyPSD 2
AmapáUnião Progressista 2PDT 22.1 pts8Toss-upPDT 2
BahiaUnião Progressista 8PT federation 81.2 pts39Toss-upPT federation 10
CearáPL 5PT federation 34.5 pts22LeansPL 6
Federal DistrictPL 1Republicanos 30.4 pts8Toss-upPT federation 2
Espírito SantoUnião Progressista 3PSB 27.3 pts10LikelyRepublicanos 2
GoiásUnião Progressista 4MDB 29.4 pts17LikelyUnião Progressista 4
MaranhãoPL 4União Progressista 31.5 pts18Toss-upPL 4
Minas GeraisPL 14PT federation 89.0 pts53LikelyPL 11
Mato Grosso do SulUnião Progressista 3PL 210.1 pts8LikelyPSDB-Cidadania 3
Mato GrossoPL 2PSD 24.9 pts8LeansPL 4
ParáMDB 5União Progressista 310.2 pts17LikelyMDB 9
ParaíbaRepublicanos 3União Progressista 25.5 pts12LeansUnião Progressista 3
PernambucoUnião Progressista 5PSB 46.3 pts25LikelyUnião Progressista 7
PiauíPT federation 3União Progressista 33.8 pts10LeansPT federation 5
ParanáUnião Progressista 6PT federation 53.0 pts30LeansUnião Progressista 8
Rio de JaneiroPL 9União Progressista 66.3 pts46LikelyPL 11
Rio Grande do NorteUnião Progressista 4PT federation 214.9 pts8SafePL 4
RondôniaUnião Progressista 3PL 23.4 pts8LeansUnião Progressista 3
RoraimaUnião Progressista 3Republicanos 210.9 pts8LikelyRepublicanos 3
Rio Grande do SulPT federation 6PL 45.9 pts31LeansPT federation 7
Santa CatarinaPL 4União Progressista 37.8 pts16LikelyPL 6
SergipeUnião Progressista 3Republicanos 214.1 pts8SafeUnião Progressista 3
São PauloPL 17PT federation 910.6 pts70LikelyPL 17
TocantinsUnião Progressista 3Republicanos 26.6 pts8LikelyRepublicanos 3

How it works

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.

Why it is sturdier than a single poll

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.

Past polling errors

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.

From votes to seats

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.

Linked races

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.

Twenty thousand simulations

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.

No probability at 0 or 100%

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.

Sources

Election results and candidacies: Superior Electoral Court. 2026 polls: surveys published by pollsters and registered with the Superior Electoral Court.

Export chambre_2026_par_etat.csv ↗ · Export the forecasts as JSON ↗

Credits

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