Jones Lang Lasalle (JLL) EBITDA (2009 - 2026)
Jones Lang Lasalle (JLL) recorded EBITDA of $402.9 million in Q2 2026, up 30.3% from $309.1 million a year earlier and up 41.0% from the prior quarter.
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Analysis
Jones Lang Lasalle (JLL) EBITDA (2009 - 2026) Analysis & Trends
On a TTM basis, Jones Lang Lasalle's EBITDA came in at $1.63 billion as of Jun 30, 2026, up 25.8% year-over-year; for FY2025, it came in at $1.47 billion, up 20.0% from FY2024.
- Annual EBITDA has a five-year compound annual growth rate of 11.0% (FY2020 to FY2025).
- Across earlier years, EBITDA came in at $1.22 billion in FY2024 (+36.7%), $893.2 million in FY2023 (-24.4%), $1.18 billion in FY2022 (-12.9%) and $1.36 billion in FY2021 (+56.1%).
- Quarterly EBITDA has ranged from $92 million in Q1 2023 to $589.1 million in Q4 2025 over the past five years.
- On a year-over-year basis, EBITDA has increased for 11 consecutive quarters, with growth averaging 28.3% over the last eight quarters.
- Peak year-over-year performance for EBITDA in the last five years was growth of 102.6% in Q1 2024, against a decline of 63.0% in Q1 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $285.7 million (Q1 2026), $589.1 million (Q4 2025) and $353.7 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | KE Holdings | 38.10 Bn | 18.80 Bn | 1.03 Bn | - |
| 2 | Cbre | 37.79 Bn | 31.56 Bn | 2.09 Bn | 605.00 Mn |
| 3 | Jones Lang Lasalle | 14.45 Bn | 12.66 Bn | - | 402.90 Mn |
| 4 | Compass | 6.85 Bn | 5.32 Bn | - | 277.00 Mn |
| 5 | Colliers International | 4.59 Bn | 3.67 Bn | 635.11 Mn | 72.52 Mn |
| 6 | Cushman & Wakefield | 2.78 Bn | 264.20 Mn | 512.00 Mn | 162.70 Mn |
| 7 | Newmark | 1.99 Bn | 1.37 Bn | - | 124.65 Mn |
| 8 | Marcus & Millichap | 1.10 Bn | 194.81 Mn | - | 4.56 Mn |
| 9 | Rmr | 593.80 Mn | 518.26 Mn | - | -4.86 Mn |
| 10 | Agnt | 586.58 Mn | 116.27 Mn | 98.80 Mn | 3.89 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 402.90 Mn |
| Mar 31, 2026 | 285.70 Mn |
| Dec 31, 2025 | 589.10 Mn |
| Sep 30, 2025 | 353.70 Mn |
| Jun 30, 2025 | 309.10 Mn |
| Mar 31, 2025 | 213.60 Mn |
| Dec 31, 2024 | 458.70 Mn |
| Sep 30, 2024 | 315.90 Mn |
| Jun 30, 2024 | 260.30 Mn |
| Mar 31, 2024 | 186.40 Mn |
| Dec 31, 2023 | 371.10 Mn |
| Sep 30, 2023 | 191.70 Mn |
| Jun 30, 2023 | 245.40 Mn |
| Mar 31, 2023 | 92.00 Mn |
| Dec 31, 2022 | 333.40 Mn |
| Sep 30, 2022 | 283.60 Mn |
| Jun 30, 2022 | 316.30 Mn |
| Mar 31, 2022 | 248.70 Mn |
| Dec 31, 2021 | 531.40 Mn |
| Sep 30, 2021 | 369.70 Mn |
API Access
Jones Lang Lasalle EBITDA API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=ebitda&ticker=JLL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "JLL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=JLL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();