NECTA performance ranking
Top 10 Primary Schools in Temeke Mc District, Tanzania – SFNA Rankings
Ranked for SFNA 2025 in Temeke Mc District, Tanzania using comparable NECTA performance data, a minimum cohort of 10 candidates and candidate-size adjustment so tiny cohorts cannot unfairly lead the table. Rankings are analytical and are not official NECTA positions.
10shown
SFNAexamination
2025results year
Top performers
#1 in Temeke Mc District, Tanzania
Results Mamaisara Primary School
View school profile →#2 in Temeke Mc District, Tanzania
Results Millenium Primary School
View school profile →#3 in Temeke Mc District, Tanzania
Results Senderwood Primary School
View school profile →| Rank | Institution | Region | District | Candidates | Pass rate | GPA / grade | Adjusted performance score | |
|---|---|---|---|---|---|---|---|---|
| #1 | Results Mamaisara Primary School PS0206101 | Dar Es Salaam | Temeke Mc | 52 | — | A | 83.77 | Profile → |
| #2 | Results Millenium Primary School PS0206154 | Dar Es Salaam | Temeke Mc | 34 | — | A | 78.81 | Profile → |
| #3 | Results Senderwood Primary School PS0206159 | Dar Es Salaam | Temeke Mc | 34 | — | A | 78.81 | Profile → |
| #4 | Results Mikwambe Primary School PS0206123 | Dar Es Salaam | Temeke Mc | 340 | — | B | 77.95 | Profile → |
| #5 | Results Uwaviute Primary School PS0206158 | Dar Es Salaam | Temeke Mc | 47 | — | B | 69.58 | Profile → |
| #6 | Results St. Getrude Primary School PS0206091 | Dar Es Salaam | Temeke Mc | 38 | — | B | 68.1 | Profile → |
| #7 | Results Cleopatra Memorial Primary School PS0206163 | Dar Es Salaam | Temeke Mc | 23 | — | B | 64.38 | Profile → |
| #8 | Results Mbagala Kuu Primary School PS0206053 | Dar Es Salaam | Temeke Mc | 625 | — | C | 59.62 | Profile → |
| #9 | Results Kigunga Primary School PS0206062 | Dar Es Salaam | Temeke Mc | 218 | — | C | 58.97 | Profile → |
| #10 | Results Mivinjeni Primary School PS0206049 | Dar Es Salaam | Temeke Mc | 145 | — | C | 58.53 | Profile → |
The ranking uses comparable data for this exam/year, excludes cohorts below 10 candidates, and adjusts performance for candidate volume before ordering schools. Schools without enough comparable data are not forced into the ranking.