diff --git a/Test/education_resource_forecast.py b/Test/education_resource_forecast.py
new file mode 100644
index 0000000..b3a9db6
--- /dev/null
+++ b/Test/education_resource_forecast.py
@@ -0,0 +1,154 @@
+import os
+from datetime import datetime
+
+# 设置中文字体支持（如果需要可视化）
+# import matplotlib.pyplot as plt
+# plt.rcParams["font.family"] = ["SimHei", "WenQuanYi Micro Hei", "Heiti TC"]
+
+class EducationResourceForecast:
+    def __init__(self):
+        # 数据文件路径
+        self.data_dir = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), 'Data')
+        # 教育阶段映射
+        self.education_stages = {
+            'preschool': '学前',
+            'primary': '小学',
+            'junior': '初中',
+            'senior': '高中',
+            'vocational': '中职'
+        }
+        # 预测年份范围
+        self.forecast_years = list(range(2023, 2030))  # 2023-2029年
+        # 加载数据
+        self.teacher_data = self._load_data('TeacherCount.json')
+        self.school_area_data = self._load_data('SchoolArea.json')
+        # 存储预测结果
+        self.forecast_results = {stage: [] for stage in self.education_stages.keys()}
+    
+    def _load_data(self, filename):
+        """加载JSON数据文件"""
+        import json
+        file_path = os.path.join(self.data_dir, filename)
+        try:
+            with open(file_path, 'r', encoding='utf-8') as f:
+                data = json.load(f)
+                # 数据文件是数组格式，我们只需要云南省的数据
+                for item in data:
+                    if item.get('area_name') == '云南省':
+                        return item
+                return {}
+        except Exception as e:
+            print(f"加载文件 {filename} 失败: {e}")
+            return {}
+    
+    def _get_teacher_data_by_stage(self, stage):
+        """获取特定教育阶段的教师数据"""
+        # 教师数据字段映射
+        teacher_field_map = {
+            'preschool': 'preschool_teachers',
+            'primary': 'primary_teachers',
+            'junior': 'junior_teachers',
+            'senior': 'senior_teachers',
+            'vocational': 'vocational_teachers'
+        }
+        
+        field = teacher_field_map.get(stage)
+        if not field or field not in self.teacher_data:
+            return []
+        
+        teacher_data = []
+        # 提取2015-2024年的专任教师数据
+        for year in range(2015, 2025):
+            year_data = self.teacher_data[field].get(str(year), {})
+            # 优先使用专任教师数量
+            teacher_count = year_data.get('total_teacher', 0)
+            teacher_data.append({
+                'year': year,
+                'teacher_count': teacher_count
+            })
+        
+        return teacher_data
+    
+    def _get_school_area_data_by_stage(self, stage):
+        """获取特定教育阶段的学校面积数据"""
+        # 学校面积字段映射
+        area_field_map = {
+            'preschool': 'preschool_area',
+            'primary': 'primary_area',
+            'junior': 'junior_high_area',  # 修正字段名
+            'senior': 'senior_high_area',  # 修正字段名
+            'vocational': 'vocational_area'
+        }
+        
+        field = area_field_map.get(stage)
+        if not field or field not in self.school_area_data:
+            return []
+        
+        area_data = []
+        # 提取2015-2024年的学校面积数据
+        for year in range(2015, 2025):
+            year_data = self.school_area_data[field].get(str(year), {})
+            # 优先使用教学面积，如果为0则使用学校总面积
+            teaching_area = year_data.get('teaching_total', 0)
+            if teaching_area == 0:
+                teaching_area = year_data.get('school_total', 0)
+            area_data.append({
+                'year': year,
+                'teaching_area': teaching_area
+            })
+        
+        return area_data
+    
+    def forecast(self):
+        """执行预测"""
+        for stage in self.education_stages.keys():
+            # 获取历史数据
+            teacher_history = self._get_teacher_data_by_stage(stage)
+            area_history = self._get_school_area_data_by_stage(stage)
+            
+            # 生成最终结果
+            for year in self.forecast_years:
+                if year <= 2024:
+                    # 2023-2024年使用实际数据
+                    # 查找实际教师数据
+                    teacher_item = next((item for item in teacher_history if item['year'] == year), None)
+                    teacher_count = teacher_item['teacher_count'] if teacher_item else 0
+                    
+                    # 查找实际面积数据
+                    area_item = next((item for item in area_history if item['year'] == year), None)
+                    teaching_area = area_item['teaching_area'] if area_item else 0
+                else:
+                    # 2025-2029年预测数据设为0
+                    teacher_count = 0
+                    teaching_area = 0
+                
+                # 添加结果，师资缺口/富余字段暂时设为0
+                self.forecast_results[stage].append({
+                    'year': year,
+                    'teacher_count': round(teacher_count / 10000, 2),  # 转换为万人
+                    'teacher_gap': 0,  # 师资缺口/富余暂时设为0
+                    'teaching_area': round(teaching_area / 10000, 2),  # 转换为万平方米
+                    'is_forecast': year >= 2025  # 标记是否为预测数据
+                })
+    
+    def print_results(self):
+        """打印预测结果"""
+        for stage, chinese_name in self.education_stages.items():
+            print(f"\n{chinese_name}教育阶段资源配置预测（2023-2029年）:")
+            print("{:<8} {:<12} {:<16} {:<20} {:<10}".format("年份", "专任教师(万人)", "师资缺口/富余", "教学及辅助用房面积(万㎡)", "数据类型"))
+            for item in self.forecast_results[stage]:
+                data_type = "预测" if item['is_forecast'] else "实际"
+                print("{:<8} {:<12.2f} {:<16.2f} {:<20.2f} {:<10}".format(
+                    item['year'],
+                    item['teacher_count'],
+                    item['teacher_gap'],
+                    item['teaching_area'],
+                    data_type
+                ))
+
+if __name__ == "__main__":
+    print("开始执行教育资源配置发展预测...")
+    forecast = EducationResourceForecast()
+    forecast.forecast()
+    forecast.print_results()
+    print("\n预测完成！")
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