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"Grants for Predictive Analytics in Child Welfare (HHS-2026-ACF-ACYF-CA-0037)" is currently closed and not accepting applications.
Grants for Predictive Analytics in Child Welfare (HHS-2026-ACF-ACYF-CA-0037) is sponsored by Administration for Children and Families (ACF). This grant supports child welfare jurisdictions in piloting new technology, specifically predictive analytics, to improve child safety and caseworker decision-making.
The funding helps transform child welfare and case management data into actionable insights, identify low-risk families for diversion, and flag high-risk cases for immediate attention. Activities include developing predictive risk models, training staff, establishing governance, engaging communities, and evaluating outcomes.
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ACF Announces $6 Million for States to Pilot Predictive Analytics in Child Welfare [](https://acf.
gov/media/press/2026/acf-announces-6-million-states-pilot-predictive-analytics-child-welfare) # ACF Announces $6 Million for States to Pilot Predictive Analytics in Child Welfare The Administration for Children and Families (ACF) at the U.S. Department of Health and Human Services today announced a $6 million investment to help state, territorial, and tribal child welfare agencies pilot new technology aimed at improving child safety and caseworker decision-making.
The competitive grant will support jurisdictions in their implementation of predictive analytics — emerging technology infrastructure that helps transform child welfare and case management data into actionable insights. The funding advances President Donald J.
Trump’s and First Lady Melania Trump’s Executive Order onFostering the Future for American Children and Families, which specifically directs ACF to expand states’ use of technology solutions, including predictive analytics, to improve outcomes for children and families.
“Child welfare caseworkers are tasked with making high-stakes decisions about child safety, often under significant pressure and without complete information,”**said Assistant Secretary Alex J. Adams. ** “Promising use cases have been tested at county levels, and we want to support scaling these interventions at the state level to improve child welfare outcomes.
” Technology tools like predictive analytics can help child welfare jurisdictions achieve a 1:1 ratio of foster homes-to-children in foster care nationwide by ensuring families are kept together, when appropriate, and placements are made only when necessary. By identifying low-risk families who can be safely diverted from the child welfare system, predictive analytics can reduce unnecessary entries into the foster care system.
Simultaneously, by flagging high-risk cases that require immediate attention, these tools ensure children who truly need placement receive it quickly — making better use of available, loving, and licensed foster homes.
The funding opportunity builds on ACF’s December 2024 roundtable convening with child welfare directors, researchers, and advocates, where participants discussed the potential of predictive analytics and current implementation success models.
Following that discussion, ACF published an issue brief in March 2025 titled Modernizing Child Welfare Technologies and Tools: Opportunities for Predictive Risk Modeling to Improve Child Safety and Outcomes.
To further support the implementation of predictive analytics, this funding will help child welfare jurisdictions: * Develop and implement predictive risk models tailored to local data and needs * Train staff on responsible use of predictive analytics tools * Establish governance structures and quality assurance processes * Engage communities and stakeholders in implementation * Evaluate outcomes and share lessons learned from the field Aligned with Trump administration priorities in child welfare, preference will be given to state, territorial, or tribal child welfare agencies that have joined, or signed a letter of intent to join, “A Home for Every Child.
”For more information about this funding opportunity, visithttps://www. grants. gov/search-results-detail/361912.
> Child welfare caseworkers are tasked with making high-stakes decisions about child safety, often under significant pressure and without complete information. Promising use cases have been tested at county levels, and we want to support scaling these interventions at the state level to improve child welfare outcomes. — ACF Assistant Secretary Alex J.
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According to the current listing, eligibility includes: State, territorial, and tribal child welfare agencies. Confirm the full requirements in the official notice before applying.
The current listing shows $6 million in total funding (approximately $600,000 per award). Verify award ceilings, matching requirements, and allowable costs in the official notice.
The published deadline was July 13, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
Grants for Predictive Analytics in Child Welfare (HHS-2026-ACF-ACYF-CA-0037) is funded by Administration for Children and Families (ACF). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
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