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The Dr. Khasro Method

Predicting new beginnings, before they begin.

ONDAS Gender Prediction is a research initiative exploring predictive reproductive modeling — combining medicine, mathematics, and computational systems to estimate fetal gender probability before conception.

ONDAS Gender Prediction — The Dr. Khasro Method

Non-invasive & reliable

Advanced predictive algorithm

Family planning support

Ethical & responsible

See it in action

Watch the ONDAS Gender Prediction Overview

A short introduction to the ONDAS Gender Prediction research and platform, available in English and Arabic.

ONDAS Gender Prediction — Overview (English)

نظرة عامة على منصة ONDAS للتحديد جنس الجنين قبل الحمل (بالعربية)

Origins

A lifetime of observation, turned into a scientific model.

The original concept was developed by the late Dr. Khasro Akram Othman, a physician affiliated with the Ministry of Health in Iraq and the Kurdistan Region. Over several decades of clinical observation, he proposed that fetal gender outcomes may follow measurable physiological and demographic patterns — patterns that could be mathematically modeled before conception.

Today, that early insight has grown into an interdisciplinary initiative spanning reproductive medicine, research methodology, embryology, and digital systems development, carried forward by the family and colleagues who shared his vision.

Dr. Khasro Akram Othman 1990 – 2026 · Founder of the original methodology

“A physician's true reach is measured not by the patients he treats in his lifetime, but by the questions he leaves for others to answer.”

Research overview

Five variables, one predictive model.

The ONDAS Repro system investigates the relationship between reproductive outcomes and a defined set of measurable variables, processed through a structured mathematical and computational model.

Parental birth dates

Blood groups & compatibility

Physiological & reproductive indicators

Family reproductive histories

Long-term demographic patterns

These variables are processed through triangulated validation — observational research, archival records, and clinical documentation — comparing predictive outcomes with documented birth data.

The platform

ONDAS Gender Prediction Software

The research was translated into a digital platform that converts decades of observational modeling into a structured, reproducible computational algorithm.

Processes reproductive & demographic inputs

Structured intake of the same variables studied in the original research model.

Generates probability-based models

Outputs are expressed as probabilities, not certainties — grounded in the underlying data.

Supports consistency & reproducibility

Built for repeatable analysis across clinical and research settings alike.

Assists reproductive planning

A supportive tool for observational assessment and family planning conversations.

Non-invasive approach Low-cost vs. genetic procedures Adaptable to clinical & research use Natural & assisted reproduction
Clinical & scientific significance

A structured perspective on predictive reproductive health.

The ONDAS Repro model contributes to ongoing discussions in reproductive science through fertility planning support, reproductive health assessment, and non-invasive family planning insights — while remaining open to independent scientific validation.

It represents an interdisciplinary integration of reproductive medicine, mathematical modeling, predictive analytics, health informatics, and longitudinal observational research.

Where the model contributes

Fertility planning support

Reproductive health assessment

Non-invasive family planning insights

Exploration of fertility-related reproductive patterns

Computational reproductive prediction models

Research development

The Akram Brothers Model

The original methodology was later organized and expanded into a formal scientific structure, incorporating archival medical records, clinical documentation, family reproductive histories, and longitudinal datasets.

A triangulated validation model

Predictive estimates are systematically compared against documented reproductive outcomes, evaluating consistency between the model's projections and real-world birth data over time.

Research Methodology
Dr. Omar Khasro Akram
Clinical Embryology
Dr. Hassan Khasro Akram
Health competency framework

Competency model for predictive reproductive healthcare

ONDAS Repro supports an interdisciplinary competency system integrating healthcare, research, digital systems, and predictive analytics — built on three pillars.

Reproductive & Clinical Sciences

  • Human reproductive physiology
  • Embryology & fertility sciences
  • Male & female infertility factors
  • Genetics & hereditary reproductive patterns
  • Assisted reproductive technologies (ART)

Scientific Research & Data Analysis

  • Research methodology & observational design
  • Evidence-based healthcare principles
  • Biostatistics & probability analysis
  • Clinical validation methods
  • Ethical standards in reproductive research

Computational & Predictive Systems

  • Mathematical modeling in healthcare
  • Predictive algorithms & health analytics
  • Health informatics & digital systems
  • Software-assisted clinical prediction models

Interdisciplinary Integration

  • Medicine, mathematics & technology integration
  • Demographic & physiological pattern analysis
  • Family planning & reproductive counseling
  • Innovation management in healthcare systems

Clinical & Reproductive Skills

  • Collecting reproductive & medical histories
  • Evaluating fertility-related indicators
  • Interpreting laboratory & reproductive findings
  • Patient-centered consultations

Research & Analytical Skills

  • Designing observational studies
  • Managing clinical & demographic datasets
  • Statistical & comparative analysis
  • Validating outcomes via triangulation

Technical & Digital Skills

  • Operating predictive reproductive software
  • Processing demographic & physiological data
  • Interpreting probability-based outputs
  • Ensuring reproducibility & data consistency

Communication & Critical Thinking

  • Explaining predictive outcomes ethically
  • Communicating uncertainty responsibly
  • Interdisciplinary collaboration

Ethical & Professional Values

  • Respect for patient dignity & reproductive rights
  • Confidentiality & privacy
  • Scientific integrity & transparency
  • Accountability in research & practice

Humanistic & Collaborative Values

  • Empathy toward couples facing reproductive challenges
  • Sensitivity to cultural & social considerations
  • Respect for informed decision-making

Innovation & Scientific Responsibility

  • Openness to scientific exploration and innovation
  • Commitment to evidence-based development
  • Motivation to improve accessible, non-invasive healthcare solutions
Research team

The people behind the model

KO

Dr. Khasro Akram Othman

Founder of the original methodology In memoriam · 1990–2026
OA

Dr. Omar Khasro Akram

Ph.D., PostDoc. — Research methodology
HA

Dr. Hassan Khasro Akram

BPharm, M.Sc. — Clinical embryology
DA

Mrs. Dania Ali Abulkarim

M.Sc. Human Reproduction — Clinical embryology
DF

Dr. Daniel Jose Franco

Ph.D., PostDoc. — Technology & systems
An interdisciplinary initiative exploring predictive reproductive modeling — through medicine, mathematics, and long-term observational research.
— ONDAS Gender Prediction
Start here

Curious whether you're expecting a boy or a girl?

The Dr. Khasro Method has guided thousands of families through 36 years of predicting their baby's gender — with 95.0% accuracy, before conception. Reach out and let's talk about your journey.

The Gender Prediction platform is reserved for registered practitioners. To request access, email us using the address above.

Bring ONDAS Gender Prediction to your clinic.

Open the platform See the accuracy data