Predictive Analytics in Child Welfare Demonstration Grants
🏛 Administration for Children and Families - ACYF/CB
Can you apply?
This grant is for organizations developing predictive analytics tools to improve child welfare outcomes and decision-making. Eligible applicants include state/tribal child welfare agencies, public universities, and established nonprofits with demonstrated child welfare expertise. Projects must use data-driven approaches to prevent child maltreatment, improve family stability, or enhance caseworker efficiency. Funding supports demonstration projects that pilot and evaluate new analytics systems before broader implementation.
Applicants must have organizational capacity to manage federal grants and partner effectively with child welfare agencies. Projects should address gaps in current child welfare systems using technology and data science. Geographic scope includes all U.S. states, tribal lands, and territories.
Key dates
- Apr 15, 2026 Applications open
- Jul 9, 2026 Application deadline in 38 days
- Sep 29, 2026 Award announced
- Sep 30, 2026 Project start
This grant is for organizations developing predictive analytics tools to improve child welfare outcomes and decision-making. Eligible applicants include state/tribal child welfare agencies, public universities, and established nonprofits with demonstrated child welfare expertise. Projects must use data-driven approaches to prevent child maltreatment, improve family stability, or enhance caseworker efficiency. Funding supports demonstration projects that pilot and evaluate new analytics systems before broader implementation.
Applicants must have organizational capacity to manage federal grants and partner effectively with child welfare agencies. Projects should address gaps in current child welfare systems using technology and data science. Geographic scope includes all U.S. states, tribal lands, and territories.
Program description
As child welfare agencies increasingly use data to inform practice, targeted implementation, analytic support, and information sharing are needed to ensure the responsible use of predictive analytics. This funding opportunity supports child welfare jurisdictions in serving as demonstration sites for the effective use and future replication of predictive analytics at the national level.
Grantees will focus on meeting the following objectives: Designing, implementing, and testing predictive analytics strategies, Building and sustaining agency capacity, Participating in collaboration and shared learning, Evaluating training and technical assistance activities.
Who can apply
Eligible applicants
- 501(c)(3) Public Charity
- City / Municipal Government
- County Government
- Public University
- State Government
- Tribal Nation
Demographic focus
Details
This grant is for organizations developing predictive analytics tools to improve child welfare outcomes and decision-making. Eligible applicants include state/tribal child welfare agencies, public universities, and established nonprofits with demonstrated child welfare expertise. Projects must use data-driven approaches to prevent child maltreatment, improve family stability, or enhance caseworker efficiency. Funding supports demonstration projects that pilot and evaluate new analytics systems before broader implementation.
Applicants must have organizational capacity to manage federal grants and partner effectively with child welfare agencies. Projects should address gaps in current child welfare systems using technology and data science. Geographic scope includes all U.S. states, tribal lands, and territories.
How to apply
Application links
Key dates & requirements
Required documents
- SF-424 (Application for Federal Assistance)
- Project Narrative/Statement of Work
- Budget and Budget Narrative
- Organizational Capacity Documentation
- Letters of Support from Child Welfare Partners
- Evaluation Plan with Baseline Data
- Data Privacy and Security Plan
- Curriculum Vitae of Key Personnel
Program contact
- 👤 Cara Kelly
- 📧 cb@grantreview.org
- 📞 cb@grantreview.org
Funding track record
Recent awards under CFDA 93.670 from the last 3 years — real organizations that won funding through this same program.
Top 10 Largest Recent Awards
-
$15,000,000
-
$14,192,178
-
$10,570,187
-
$7,983,345
-
$6,000,000
-
$6,000,000
-
$6,000,000
-
$4,992,412
-
$2,852,864
-
$2,852,578
Top States by Funding
- DC 3 awards $20.6M
- CA 6 awards $17.0M
- MN 2 awards $16.5M
- MD 2 awards $10.7M
- CT 1 awards $8.0M
Source: USAspending.gov — federal spending transparency. Data covers last 3 years.
Funding history
Annual funding for this program — Federal obligations (CFDA 93.670). How funding has trended year over year.
| 2024 | $15,178,672 | |
| 2025 | $12,499,849 | |
| 2026 est. | $12,499,849 |
FAQ
Who can apply for this grant?
State and tribal child welfare agencies, public universities, nonprofits, and public-private partnerships with strong child welfare credentials. Applicants must demonstrate capacity to manage federal funds and conduct rigorous evaluation.
What types of projects does this grant fund?
Projects that develop, test, and evaluate predictive analytics systems for child welfare decision-making. Examples include risk assessment tools, family engagement systems, or caseworker support platforms.
What is the typical funding range?
Demonstration grants typically range from $500,000 to $2 million annually, though specific amounts vary by year and project scope.
How competitive is this grant?
Highly competitive. Applicants should demonstrate strong technical expertise, partnerships with child welfare agencies, and evidence of impact potential. Rigorous evaluation plans are critical.
Are there matching fund requirements?
Many HHS-ACF grants require cost-sharing. Check current solicitation for specific matching requirements, typically 10-25% of total project costs.
💡 Tips for applicants
- Build partnerships with state/tribal child welfare agencies early. Agencies must champion the project for success and sustainability.
- Focus on real child welfare challenges with measurable outcomes. Show how predictive analytics specifically solves current problems in the target jurisdiction.
- Design rigorous evaluation from the start. Include baseline data, control groups if possible, and clear metrics for caseworker/child/family outcomes.
- Address data privacy and ethics thoroughly. Explain how you'll handle sensitive child data securely and ensure algorithmic bias mitigation.
- Plan for sustainability and scaling. Demonstrate how the system will be maintained and expanded after grant funding ends, including costs and partnerships.
⚠️ Common mistakes
Vague technical approach without clear connection to child welfare outcomes. Lacking partnerships with actual child welfare agencies or unrealistic buy-in assumptions.
Insufficient attention to data privacy, security, and algorithmic fairness concerns. Missing credible evaluation plan or unclear metrics for measuring success in real-world settings.
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